If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Pierre. It’s been a massive week this week. The week started with a bang. We predicted Chat GPT were going to have their paws their MITs on the purchasing experience for consumers by the end of the year. And it happened October one, was it? No, even sooner than that. It was end of September,

Piere: September 30th, I think. September 30th, right on Monday. I believe they, they release that, Shopify and OpenAI will start a partnership that you’ll now be able to shop on chatGPT.

Angie: This is massive brain blasting, blasting wonder.

Jeff Bezos had a slightly nervous feel in his stomach. when chat GPT started picking up traction, I thought I’d never, never could have imagined a world where Google would become irrelevant. But we certainly never imagined a world where potentially Amazon is going to have its toes bitten, at least.

Piere: Yeah. You know, we’ve seen that in history, right? It’s, it’s not, it’s not whoever is best, it’s whoever move first, right? Whoever is moving first will sort of have, the, the biggest market share. And I think in, in such a big, breakthrough in such a big change of how you do something and how you change your habit, as in online shopping, that is definitely the case, is whoever’s gonna move first and chat GPT and Shopify, I think just surprise everyone.

And you know, you and I predicted that it will be in the near future. but I was thinking more, maybe early. To mid next year, not. Before Black Friday. 

Angie: I feel a bit ripped off that I, uh, overestimated something. yeah, it’s a amazing, um, amazingly fast-paced thing. I mean, we, in our own developments have got wishlists of features we’d like to see out of chat GBT to make it more open.

AI or some of its, counterparts that we use in various parts of the, our product and development. Literally we just have to wait for a few days or a few weeks and bang, there they are. It’s just that the pace of this change is incredible. And like you say, it’s a race to see who’s first and, and that race is going to become probably something that attractions have to pay attention to because.

One can only imagine that if there’s an attraction A that has, AI enabled ticketing, um, purchasing process and attraction B that does not, given chat GPT doesn’t operate in quite the same sort of transparency and ethics as like a Google search I presume that it’s going to prefer the one that it can clip the ticket on, literally.

Piere: Mm. Well, let’s, let’s that sink in for a second because it means that in maybe a few weeks, maybe a month top, what are we saying right now? Is that someone, right now a museum on art gallery, or, you know, a theme park, but I’m thinking probably Museum and IES right now could be selling their artwork on chat, GPT as of next month.

Angie: In store. Yeah. So Shopify have already, announced their partnership with OpenAI. Right? That was one of the press releases that came out this week. so yeah, in terms of merch, absolutely that’s the thing. and yeah, I think the challenge will be up for the ticketing vendor is next to see who’s gonna be first.

Literally Absolutely. To, to do this.

Piere: Absolutely. I think it’s just opening that door that, that we were, you and I were, were talking about a few episodes back where yes, we’re changing our behavior on how we plan things, but we still need to take that step of, you know, going on a website, interacting with that website, clicking away.

Picking if it’s two adults and one child, et cetera, uh, very much like, you know what you’ll do when, when you show up online. Now what we are seeing is that they’re removing that step, right? You don’t need to go on that website. You don’t need to do this extra clicks. And it’s starting with e-commerce, as you mentioned, is what’s next.

And, and you’re right, I feel what’s next is gonna be that experience based of to be able to book a plane ticket, to be able to book a ticket to a museum, to a special exhibition. Theme, park pass, you know, season pass, et cetera, et cetera, et cetera. and yeah, that, that’s, that’s just gonna change the way people interact with, with these products.

Angie: It’s been a crazy year actually with tariffs and recessions and inflation and all of these sorts of things happening in many different places in the world. And this is just one last sort of plot twist at the end of the year to, to carve that out. And, uh, one of the things I wanted to talk about today is that sort of, visitor spend, whether it’s retail, whether it’s food and beverage, whether it’s admission, Sort of what that consumer wallet looks like when that visitor comes on site and how to think about pricing and price increases and and so forth to maximize your value per visitor, your average revenue per caps, yields, um, but also your margins. and, you and I were sitting in a, a customer meeting with a, visitor attraction this week where.

We were looking at their compound annual growth rate, so the KAR of, per caps by their various lines of business. So admissions, we’re looking at retail, we’re looking at food and beverage. We’re looking at the total visitor spend over the course of like, maybe five years. And it was a fascinating sort of deep dive into how their, average, Revenue per visit and its breakdown was padding out over that timeframe and how that sort of translates into average price point, sort of basket size, that actual spend, that actual margin sitting behind it, given everything that’s happened behind the scenes. behind that story of that data point, and it it got me thinking about like how.

how to analyze for, determining whether you need to increase prices, whether you’re sort of keeping pace with that. what, what are your thoughts on when the sort of the moment comes up to, uh, know that this is a, an area that needs analysis and potentially change?

Piere: That’s such a good question, and I think you’ve mentioned line of business earlier, and I think, you know, it will depend on the line of business that you’re looking at.

and some of them may be more indirect line with price change down, you know, down the track essentially. I’m, I’m thinking FNB, right? FNB would be likely to be more, aligned with the inflation of. primary products, you know, your, your vegetables, your meat, et cetera, and it is likely maybe to be impacted by inflation a lot quicker or than than your retail and your admission prices, for example, right?

When you think about how often you restock your FM B’S item against your retail item, you can understand that. The price is likely to change a lot faster than, than in retail and and ticketing.

Angie: Yeah, that’s so true. We’ve seen the tariffs come in, which are obviously gonna hit the retail, merch business, harder than anywhere else, and their visitor attraction, although, you know, probably some of it will come into that food and beverage as well. Because a lot of that food is, imported, for some of the fresh products. in particular. But, you’re right, like retail stores maybe stock once, sometimes twice a year. It is not sort of a weekly thing. And so we’ve seen a lot of that sort of impact of an, of those tariffs yet to hit some of the merch, lines of business. And even where it has been, a lot of attractions have been shielding the, the visitor from some of that tariff. but if we look at the sort of consumer price index or CPI overall, like in the us. it’s sitting at about 29, uh, sorry, 29, 2 0.9%. Gosh, 29. We’d all be in trouble. 2.9% year on year. up until August.

That core inflation is sitting at sort of 3.1, so that’s exclusive of food and energy. but for food and beverage in particular, it’s sitting as high as three point. 12% year on year. So that sort of food, either, whether it’s at home, food like groceries or away from home food, like, you know, restaurants, cafes, et cetera, that, that away from home food inflation does lag a little bit.

It does behave a little bit more differently, um, the grocery inflation as well. and there’s a lot of sort of complexity. And agricultural factors and things that plays into that as well.

Piere: Yeah, 100%. I think, you know, you’re right. Like in term of the numbers from, from 2020 to 2024 CPI roles are right.

You know, 21%. Food. CPI was about 24%. so I’m gonna do a percent of a percent here, and all the data analysts are gonna scream at me. Uh oh. But to me, that’s an extra 10%, right? or 10% quicker. So, it is a big difference. I know we are talking about, you know, is, you know, single digits, um, defense, but, but it is a big difference.

And you’re right. Like we, we’ve seen in Europe especially. there’ve been a lot outcries, you know, in, in countries like France, for example, where I’m from, where, you know, farmers are hit with severe regulations that increase cost of, producing food or, or meat. and people are either absorbing this cost and offsetting this cost to the buyers, or people start to buy.

In other regions of the EU, to get cheaper products, but that also involves transport. so overall it’s, I feel like the, there’s more of an impact. There is a compounding in impact around, how can I say that? Because there’s more intermediaries, I think like the food cost will be compounded in term of how many times someone needs to offset the extra cost to the end consumer.

And versus retail, maybe there’s less of that, right? Because you’d be, going factory supplier, supplier, attraction for example. And that’s a gross explanation. But I think that could be potentially explaining, why these prices are increasing a little bit more as well.

Angie: Yeah, there’s kind of three different rhythms in there.

you know, that food and beverage price increase, which typically goes up quite quickly, that retail price increase, which typically sort of is still increasing at a relative rate, but a bit slower than food and beverage. And then when we think about admission price points, a lot of visitor attractions don’t review those for years at a time.

And so we’ve sort of got three different, paces at which we review pricing. And I think when sometimes when you take a food and beverage outlet and you tuck it under an attraction, you can sort of naturally slow down. What would otherwise be the normal rate of pace of change, of that price increase for food and beverage, because it’s now part of an organization where the base sort of revenue coming from admission is typically, reviewed less frequently, , than a, than a traditional food and beverage outlet.

And so I think sort of just being really aware of, of those changes. I know like every time I go to buy a cup of coffee, it feels like it’s another 50 cents. I love a good flat white, here in New Zealand, which, is making its way through America. I notice every time I go to New York or DC or even LA these days, I can buy a flat white.

So, uh, we are slowly taking over the world with our milk coffee. You know, like once upon a time it was $4 and then four 50 and five and, and now like, you know, you, you go in at $7 or even eight, or eight 50 and you sort of take a big breath in. but you know, this is the sort of rate at which. You know, food and beverage pricing is, has been increasing over the past few years that it’s effectively doubled now.

The same isn’t true for an emission product. and so, you know, one, it’s increasing the slower rate. Two, it’s increasing at a lesser rate. And so I think sort of being really hyper aware of the different, pace and, and, pressure that you’re putting on your different pricing for those three different lines of business and parking and accommodation and things if you’re dealing with those as well, a whole different kettle of fish. Just being aware of, of those is really important.

Piere: So interesting. So I’m gonna put you on the hot seat here.

If you were to reconsider your pricing for admission as an attraction, how often will you do it? How often will you look into it at least?

Angie: Well, I think, I think it should be a litmus test at least once a quarter across all elements. And for me, some of this would come down to mission, you know, is this an issue of accessibility or are we here to make profit?

and I think then some of it would come into, uh. The tolerance level, like one of the first places I like to go is into voice of the visitor. have a look at the amount of, say, food and beverage complaints that you get that are related to pricing if you’ve got the volume to support that. And compare that to industry benchmark because people are always gonna complain about things being expensive.

So it’s like the degree to which they complain and how tolerable that level of complaint is. If I was here to make margin, then you know, I would say I would sort of push that, you know, as a little bit further than I’m comfortable with. if I’m here. On accessibility, then that’s going to be more driven by my commercial sustainability needs.

But I think sort of, what we pay a lot of attention to things like, you know, average revenue pivot, the per caps and how much shows are increasing, but paying the same level of attention to margin is equally as important. And so one of the core, key performance indicators or KPIs that I like to look at is the net value per visit.

So. Total revenue that we’ve made, from the visitor admissions, retail, food and beverage, whatever. And then the total costs, and we can consider the costs either as like a gross margin. So it’s just sort of the cost of supporting those functions or we can consider it in totality. So all of the sort of overheads and things like that, of our operation as well.

And just keeping an eye on that net value per visit, which may be negative for, hopefully not many commercial attractions, but certainly for some cultural institutions if we are thinking about sort of other forms of, uh, of income that they receive in terms of grants and so forth. But preferably for most it will be positive.

And just keeping an eye on that and seeing how that is changing. Because if I come back to this example that you and I were looking at earlier this week, when we are seeing like, you know, for example, that food and beverage, Figure that was increasing at a lesser rate than retail by quite, quite some way, over the course of those years, the, the biggest story that was sitting underneath that is the fact that, as you say, those, those prices of the goods that are going, or the products that are going into producing that food and beverage have been increasing at a much higher rate. And so, presumably that’s pressuring and pressuring and pressuring that margin.

So, so that’s, that’s what I would use as that net value per visitor, sort of that sense check. And then sort of break that down into some of my margins for each of those lines. Test that against my consumer tolerance. I think sort of working out, we always think that people are more sensitive to pricing than they actually are.

And of course, if you ever ask anybody knows, it’s too expensive, the answer is always going to be yes. So it’s that really delicate art of sort of pushing the envelope as far as you can get away with it. if that’s what you’re after or if that’s what you need.

Piere: Yeah, 100%. I like what you’re saying, and it there is sort of ties to what you were saying about the price of the coffee.

I guess the, the reason why you’re still buying coffee, even if it’s pushing that $8 mark, is that it didn’t go from four to eight in a month’s time. It gradually increased. Right. So I wonder if, like, the analogy that you take into reviewing your pricing every six months is also the same, right? Like you want to.

Potentially increase that gradually. So if your price of admission is 15 and you haven’t touched it for four years or five years, making it 25, all of a sudden maybe almost like a, you know, a tag shock to people that are gonna buy a ticket. So, reviewing it, often increasing by, you know, a couple of dollars, $3 at the time, it is less of a shock and it creates that habit, right?

It would also be different for heavily you, you know, international market, visitor attractions, right? You know, when you’re on holiday, maybe you pay a little bit less attention to the price of a specific attraction and doesn’t, I mean, I’m not gonna say it doesn’t matter because it does matter if it’s 10 or 15 instead of 15 euro.

Maybe it will matter less if you are an international choice, for example, than if you’re local and all of a sudden your local, you know, cultural institutions brought their prices by 10 or 15%.

Angie: And to bring that back to your first point, the locals are probably going to notice the heavier jumps. even if they are more infrequent, where the tourists obviously won’t ’cause they’ve got no precedence to compare them back to.

I sound like a hypocrite saying this because we’ve only put our prices up at Dexabit once, in our history. But, uh, definitely I’ve met, you know, dozens and dozens of visitor attractions who will quite commonly say, oh, we haven’t reviewed our pricing in X number of years. and then when they do, they do do those big, leaps from like 19 to 24 or 24 to 29, or they’ve gotta get up over 30 and it’s suddenly 34 50 or something like that, rather than those more incremental things.

And, and like you say, even sort of between admission retail and food and beverage, even between admission of like. You know, your local versus your, your domestic or international tourist pricing. like you say, you can sort of consider different, pricing, different, different elements or different paces of increase, on those, if you’ve got the ability to, to split and, and probably another kind of strategy is to look at more variable pricing.

So quite often a lot of people leap to dynamic pricing where. They’re doing it based on demand without sort of the intermediary step of going from fixed into variable pricing where, you know, maybe you do cheaper Tuesday or mornings or you know, maybe Mondays are always quiet. So you give those a different rate or

School holidays might be more expensive than not, and, and all of these sorts of things, that gives you some more data to be able to analyze, your price sensitivity and elasticity. But it also, you know, gives you that ability to control things a little bit tighter and to push the, the envelope a little bit more where you need to without sacrificing some of the visitor volume or accessibility. Where that’s important.

Piere: I was just, before you mentioned dynamic pricing. That’s something that I’ve. I’ve seen before, right? You, you see people going from zero to a hundred like that, right? As in like someone or an institution that haven’t reviewed their pricing in several years and then all of a sudden they realize, oh my God, we haven’t touched these prices in X amount of years.

And then they’re like, okay, cool. We’re gonna go to dynamic pricing straight away. Yeah, let’s get a blow torch, right? And, and there is there that step in between, right? Like the, because dynamic pricing we’ve had, I think we’ve had that conversation before right It’s a very, very, very sensitive topic in my opinion, right?

No one likes to go on a flight booking website in the evening and getting the right flight, and it’s, you know, 350 bucks and you’re like, you know what, before a book, I’m just gonna have, I’m just gonna think about about it overnight. I’m gonna have a sleep, and then I book you tomorrow morning and you go tomorrow morning the next day, and guess what happens?

Exactly right. How frustrating is that? So imagine that before attractions right now you don’t have a, you know, you don’t have a choice. It is D-Day and you’re about to go out with your kids and the price of the attractions went up 15, 20 bucks overnight and you didn’t book it last night because you were tired.

So overall it is, it is a sensitive topic and , I don’t know how I feel about, about dynamic pricing for visitor attractions, but nonetheless. People are taking that step, right? They’re going from, we haven’t touched prices to, we are gonna implement dynamic pricing. and there is, there is a step in between that.

There’s a step of, well, actually, how long ago did we review our price? Then second question is, if we have institutions around us, what are the prices? How long are people spending in these attractions and how long are they spending at our attractions? They spending the whole day, half a day, a few hours.

so you can sort of understand, you know, the, the, your price compared to other attractions around you. and then you can make that decision, right? Yes, we are a lot cheaper to other attractions based on the experience that they offer or. We are on par or we are more expensive. and then you can, you know, it’s almost like if you’re more expensive then you can think of dynamic pricing.

‘Cause you’d be like, I wanna compete with these other attractions. and I want to boost my, my slow times, right? My, my days that are very slow. My hours are very slow. and I want to increase capacity on these days. but The good news I feel, is that admission pricing is fully controllable versus retail and FNB, you’re depending on that supplier not raising their cost.

You are depending on that, you know the price of eggplant not going up, if you’re serving eggplant. That is, You know what I mean? Like I, I feel like admission is a lot more comfortable there. There’s like that one aspect of the business where you have full control, until something like the, a minimum wage, you know, increase in a specific country and then boom, you hit with an extra expense and then need to think of.

You know, putting up your prices or the cost of maintenance or specific ride is going up, or it needs to be maintained more often than one originated planned, et cetera, et cetera. But I feel there’s a little bit more control there. What’s, what’s your take on that?

Angie: Yeah, I think it, emission revenues, uh, it typically got like very high incremental margin.

So especially on days when most of your fixed costs are already covered, you know, different, different If you are, say. Warner Brothers, uh, studio tours in Hollywood where every 10 visitors you’ve gotta put on a new tram with a driver and everything else. But you know, if you are LACMA down the road, you know, once you’re building and security and utilities and all of that sort of thing are budgeted, allowing more visitors.

Through the doors or getting more visitors through the doors, or getting a higher ticket price for those visitors through the doors. That tends to have a, a very low marginal cost. other than maybe some incremental staffing and wear and tear and things like that. And so, I think because of that, like,

the admission is the highest, margin lever to help you raise revenue and profitability at the same time. so I think there’s this idea of sort of preferring to push on admission versus some of the other, lines of business, because that sort of gives us that, that better sustainability. But you know, like once the capacity is there each, each incremental visit, uh, visitor is almost like.

Pure profit, minus those variable costs. so I think, I think that that’s sort of something you often talk about the visitor having like a fixed wallet when they turn up. And sometimes that can also include like the cost of getting there or parking or buses or whatever they’re doing, or bringing their lunch even if they’re not eating on site.

And so I think sort of thinking about that when you were thinking about how your different lines of business might cannibalize each other and then be very strategic about where you push those price increases, to make that work, in a way that’s going to deliver the highest margin. particularly if you are dealing with like a third party operator maybe handling food and beverage and therefore even of the margin, you’re only getting a share of it.

Right. So, sort of thinking about how that’s going to best. Benefit your organization versus some of those consumer behaviors.

Piere: That’s so Right. And I think, you know, the, the benchmark analysis that will be launching very soon around destinations and around how destinations perform on generative AI platform, but also, you know, how much people should plan to spend, whether they’re going to X or Y locations, which sort of help.

Institutions make these decisions, right? How, how much are people planning to spend when they come? they have that fixed wallet, they have that budget. They may be flexible on that budget, depending on, again, if they are local and international visitor and so on. but how do I fit my products and my different offerings within that fixed wallet?

That’s gonna be the question.

Angie: Yeah. And then sort of how does that margin break down? So if we can imagine that that, you know, typical gross margin or incremental margin is like exceptionally high for the admission. After your fixed costs are coverage, and then maybe your typical net margins potential is somewhere around the like 20%, across your full operations.

Maybe it’s sort of that mid to high, single digits depending on what your cost structure is. But then if we can pair that to like retail. And food and beverage retail, we’re probably talking about an average of like moderate to high, like 40 to 60% on your gross, and then it’s gonna end up somewhere around maybe five to 12.

on your, net and then food and beverage will probably end up somewhere like 60, 70% on gross, but then again, like somewhere around that five to 10% on your net. So, and, and then like if we’re halving that or whatever, how it’s being split up with revenue share on the, on either of those business lines, like it just makes more sense to focus that, that spend into the admission just for the margin benefit.

Piere: Yeah, for sure. No, I agree with that. I agree with that. Look at your prices every six months. make a small increment if necessary, and people won’t be scared of the price. Right. I guess.

Angie: And if you are going to go dynamic, I think there’s some. There’s the obvious ways to do that. You know, the, the airlines have done it, the hotels have done, as you mentioned, and attractions.

We do tend to see it more in the capacity limited, attractions. So things like, for example, if I go, if I go up a tower in New York to look at the view. Chances are that’s going to be a dynamically priced visit versus, and sometimes with like zoos and aquariums because of the popularity, you know, those can be, ones to go for.

But like if it’s in my local art gallery where I’m wandering around and there’s quite a bit of space for everybody else to wander around, like the, the business model doesn’t make entirely good sense there, and there are some players that are doing it in food and beverage or starting to or thinking about it, and the same as some of the retail as well.

There’s some more subtle ways to go after it. It’s like you could do like this sort of happy hour type thing because that’s more like explainable to a visitor versus like, you know, suddenly seeing prices jump and things like that. Particularly in that food and beverage setting. So there’s some ways to sort of very subtly brand what might be sort of considered at least an element of dynamic or variable pricing, but just sort of make it come across different as well.

All about sort of how that message is delivered.

Piere: Yeah, for sure. Did you mention something about, like potential packages when people buy an admission, as in you buy an admission and you buy, you know, or you pre-buy food at the cafeteria or the cafe, et cetera. have you seen that very often?

Angie: Yeah, I know it’s popular with, um, FECs and, some of the lbe, uh, so the Family Entertainment Center and uh, location-based experiences.

I know you’ve, you’ve had a few of these with the kids’ birthday parties and things like that, right?

Piere: Yeah, yeah, yeah, absolutely. I’ve, I’ve seen it very often and I think. it is a great way for the business to forecast how much money they’re gonna make on that specific day because they already know how many muffins they need to buy, uh, when there’s a birthday party, et cetera.

But I wonder if there is a way to, or if there are businesses out there that are expanding that to general visitation of all, and that would, you know, that increase that amount of control, and cost reduction because you are controlling your waste. Your potential waste a lot more than, you know, just waiting for people to turn up and see what they get at, at the cafe or what they get at the retail store.

Angie: Yeah, that’s really important. If you have got a decent amount of advanced pass reservation, and particularly if those are from larger groups like children’s birthday parties or corporate events or anything like that, like getting as much of that advance notice and, and preferably cash commitment, is a fabulous thing to do if, if they’re not already doing it.

and yeah, absolutely. I can totally see that bleeding into the consumer experience. And I think it’d be, it’d pose a really interesting thing for the consumer, sort of psychology, the consumer wallet, when they’re thinking about their visit. I know for a lot of visitors, for example, you know, to your point of.

That you, you often talk about of, you know, the visitor having that set budget in their mind, they come to the attraction, they buy the ticket, they, you know, think about I’m gonna spend my $8 on my, coffee. and therefore there’s no, there’s not sort of money in the kitty for, the plush toy as we are going out.

versus like, for example, some of our attractions have got sort of collectible souvenirs that might be even like. Over $10,000. So they’ve got these, beautiful like five figure, sum products sitting in the retail store. And for some visitors it’ll be that trigger that it comes out of a separate psychological wallet.

so I think maybe sort of breaking up that visitor spend that some of it’s committed earlier and then some of it’s. sort of more on the day, you know, potentially we are drawing on two different, um, but like the dessert stomach, um, two different sort of spending, um, thought processes, in the consumer’s mind.

Piere: No, you’re totally right. And I can see how, for example, people. Um, some folks are already doing it, for exhibitions, right? Like you, you have some folks, out there that, have special exhibitions on. You can buy a special exhibition ticket if you want, but you can also buy a special exhibition ticket, and the catalog for that exhibition at the same time on the website, for example.

And that’s like an easy maybe upsell. And then as you mentioned, you know, it’ll be harder to push something that, impacts you on an emotional level after you’ve seen the exhibition such as, you know, an item that really resonated with you. when you got that exhibition and you saw that piece of artwork and then like it resonated and you want to buy an item that, that reminds you of that piece of at work. 

But yeah, I think, I think you’re totally right. It’s, uh, Popular in, in some institutions and some type of institutions, maybe less in some others. but I think overall a great way to pre-book your revenue, a great way to plan, and, and pre-book that revenue and secure that revenue early

Angie: and for food and beverage.

Also, a great way to reduce some of your wastage as well. If you know what people are after, particularly on some of that, perishable inventory.

Piere: Absolutely. I think it’s, is

Angie: it dessert? Stomach a real thing, Pierre? Is it scientifically proven? I feel like it is?

Piere: I’m not sure. I think that’s just Angie thing. I don’t know. Uh, no. I feel like, yeah, I think, we can say it’s, um, it’s scientifically proven.

Angie: Pierre, what’s the one thing we haven’t talked about yet when it comes to pricing on different lines of business and the attraction?

Piere: Well, I think earlier you mentioned a voice of the visitor and the data that we have. One of the topic that. I usually look at is as you mentioned, price, but then price related to, to quality, right?

And if we take the F&B sector for an example, and if you are lucky enough that if you can afford to offer more than one type of dining experience At your institution, uh, you may have that tech wake out outside and you may have that sit down restaurant. I think like if there’s a, a huge change in experience and in expectation when people are sitting down and they’re gonna pay a higher price, and then I think you will agree that the quality also needs to be higher and also needs to be leveled up.

And I feel like this is where we get a lot of these potential complaints, right? Is that when people. Choose to go that level above on the f and b, right? For example, at an institution, but don’t actually necessarily feel like the quality or the service was adequate to that level above, what do you think?

Angie: It was expensive for what it was? Yeah. And how often do you hear that? Right? Yeah. And I can clearly see when I look at some analysis, on, food and beverage and pricing and value and, and cost and things like this, there is that clear. Emergence of, of both quality and service or like experience. so there’s the sort of difference of paying a lot for a hot dog.

Is this what they’re called? Corn dog, whatever they’re called. Uh, paying for one of those at the cafeteria, versus like if you’re seated in front of something on, on a plate. So like, if you are going to push that envelope of pricing, think about how you’re doing it in relation to both the quality of, of the food and also the quality of the experience of the food.

And potentially doing those in two separate locations if you have that. Available to you and your attraction to be able to differentiate them is a great way to sort of, play with that perceived, quality, of food or experience, you know, the plated versus the, the paper or, The, the white cloth versus the cafeteria bench.

All of those sorts of things is the table surface versus the, countertop. they all make a difference. and you can do almost the opposite, in retail. Like pulling out some of your more expensive items into a popup, can be a more effective way of doing a popup than pulling out some of your cheaper items.

So I think sort of playing with that place and, and that style of experience as it comes into retail and food and beverage is great. some tips here on, on analyzing this data. I would, take a look at your average, price for your, products that you’re moving in, both retail and food and beverage, and then sort of look at how that’s interrelated with your average basket size.

So the number of items and that, average, spend per visitor, again, as it relates to retail and as it relates to food and beverage. And look at the range as well and sort of look at That bell curve or lack thereof that you might be experiencing on your range? I know for a lot of visitor attractions, they end up selling a very high volume of postcards at like, you know, 95 cents each or whatever they might be pulling for them.

And sometimes that can be a distraction and, and a very low margin saying it’s a nice. I guess for a visitor to have a take home of their visit, but if you’re selling things less than a buck each these days, it’s hard to sort of see the, the, value to your attraction in doing that.

Piere: The tote bags, the postcards, the magnets, right?

Angie: Yeah.

Piere: These are the ones that are, yeah, that’s, that’s so interesting. That’s so true.

Angie: Unless there’s sort of a brand benefit for yourselves in doing that, then you might wanna question some of that. I mean, some of the tote bags as a prac, practicality I guess as well. but yeah, we do see that often those, those bell curves aren’t quite belled.

And there’s just too many, um, are too higher volume of, of cheaper items in the store that are discouraging some of that heavier spend.

Piere: Absolutely. Absolutely. So true. Thanks for that.

Angie: Well, I’m about to go out and get myself an $8 coffee. So, uh, until next time, Pierre.

Piere: Thanks, Angie. Until next time, enjoy your coffee.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Ravi Chandra and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: The sky’s blue outside, but it looks like we’re in for a stormy weekend. We had to hit the record button very quickly ’cause Ravi was already getting deep in organizational intuition.

Ravi: That’s right.

Angie: Talking about storms on the horizon.

Ravi: We were just talking about how intuition is almost like when seasoned sailors can look out at the sky on a morning and I’ll be like, ah, it’s a stormy one, it’s gonna be this afternoon. And they, they have this intuition, this gut feel where they can recognize the signs before all of the equipment or they get the weather reports even coming.

And in many ways, what we’re talking about today is how organizations can also behave in that same way, and sometimes it’s necessary to use a bit of old gut feel, especially in times of uncertainty or just huge disruption like we are today with AI changing almost everything about what it means to be a business, especially in the technology space.

We can’t use data and and evidence because it, it doesn’t exist yet. We haven’t created that base as a society or a collective to, to lean on huge data sets to, to prove what we should do, and it’s a completely different world and that we’re operating in. Mm-hmm. That’s where it’s sort of back to the, the gut feel and intuition.

Angie: I can hear my father’s words in my head of red sky at night, the sailors delight. But I think I was when we started to get into the generative AI age, and I was just reflecting on this this week ’cause we moved into a new office.

Ravi: Mm-hmm.

Angie: And it reminded me of the times of the previous move into the new office and where technology was at at that point.

You know, I think it was three years ago.

Ravi: What was new then?

Angie: Well, we were working in machine learning. We were sort of setting up a new machine learning framework at that point in automation sort of harness. And we were doing voice of the visitor back then in natural language processing and having mixed results.

It was good but not great, and I remember when. Generative AI opportunities came in a knocking, would’ve been a year later, maybe two years later. I was a little bit resistant at the beginning. Because things with machine learning and, and natural language processing back then were a lot harder than anything is today.

And it seems like at the click of the button, we’ve got access to so much more times a thousand.

Ravi: That’s right. I, I do remember those early days where we were experimenting with, with generative ai and I think, chat GBT had only just, just landed. And it was, it was interesting. It was fascinating because it felt like it could do so much, but it was also actually quite bad and wasn’t quite ready to be embraced in the way we we are today.

But, I think it was quite natural to to be resistant.

Angie: Mm. Nowadays I see faults and chat GBT and think they’ll probably fix this by next week.

Ravi: That’s right. I

Angie: My favorite fault of it’s at the moment is that if you’re doing some extensive work over a longer period of time, it, it hasn’t quite worked out how to save the file and drops the file constantly through the conversation, and it can be really frustrating.

But I think these sorts of things like six months from now will be table stakes for. Conversational insight, at least

Ravi: That’s right. It reminds me of a, of a quote from William Gib Gibson, who is a sci-fi author. I think he said the future is already here. It’s just not evenly distributed. And I really love that.

’cause I think it really rings true. And, and organizations will probably face it whether they, they realize it or not.

Angie: Yeah. You always have the best quotes in our podcasts, really distributed across chat GT features, as well as its users, huh?

Ravi: Yeah.

Angie: So what does organizational intuition mean when we’re talking about ai?

Ravi: So what I think it means is as a business and that sort of. At both the collective and leadership levels, there is a strong understanding amongst everyone about what an AI can do, and especially what an AI can’t do. Mm. And they can start to see opportunities where AI can be harnessed and embraced today, but also where.

It’s heading and it’s sort of a shift in, in direction of travel. And what makes this really hard is because a lot of these opportunities might not have been realized yet exactly as you say, because OpenAI haven’t invented it or they haven’t added that feature. But I think, you know, you can see we are going in that direction and it will be a reality.

It means that you need to take a quite nuanced approach to to leadership and how you create and adopt new processes. And I think for us at Dexibit, it’s really meant reevaluating almost every part of of our own business from both our product and how users might interact with it,

Angie: how we make it,

Ravi: how to make it, but also our own roles and responsibilities.

Because they’re probably going to change as we adopt and transform.

Angie: I think there’s, there’s almost that middle ground as well of knowing what it can do, what it can’t, and knowing when it could probably do something. You’re just not approaching it the right way. And I think you taught me this, like sometimes I would try things out and chat to BT and deliver me a horrible result and I’d get frustrated, throw it in the bin.

Say, oh, it’s terrible at that. But actually it was the way I was prompting it and we hear all about like the skills of the prompt engineer, y, YY, but I think it’s really easy to lose sight of that in the moment of a task that you’re doing versus like seeing how carefully you can create, curate your prompts and how you treat that as like an iterative process.

Was sort of a light bulb moment for me and watching you do it and then working out how to do it and then working out how to teach that as well.

Ravi: Yeah, I mean that’s, it’s funny you say that because I think. The script is flipped. Where now I feel like I’m learning from your own prompts and how you’re using AI and chat.

GPT be because it’s a sign of how quickly these things change and how what was once a good prompt, uh, actually is no longer. Mm-hmm. So, we are discovering and learning all the time, and I think that comes back to that, that sense making and intuition aspect of, of AI It’s gonna require these, these personas.

That will embrace, uh, exploration and experimentation and, and really understand you know, what, what it can be for.

Angie: We have two quite parallel experiences. Me through the UI and, and you through the API in some ways as well.

Ravi: That’s right. I think sometimes in the using the ui and the API, like, they’re quite different experiences.

So my primary experience is via, is for building our product and how we use AI to, to improve that process or at least enable new features. But there are so many different considerations there when it comes to building a product around latency and, and cost and, and quality of result, which is quite different to the user experience from when you’re, talking to, to an AI agent.

Angie: I remember I was sort of reflecting back last night on organizational intuition. It’s a phrase I’ve heard you use a few times around AI And thinking one of the things that, the feelings that you get around it is like the feeling of that exponential growth that you mentioned. You know, where you can see it, feel it in your own use of, you know, I used it a couple of times a week and then I used it a couple of times a day, and then it became a few times an hour and, and then sort of seeing that same journey through the team and hearing it mentioned once every few weeks, and then once a week, and then once a day, and then constantly throughout the day. And you definitely feel that airplane taking off of, of how AI’s being used amongst the team in so many different ways and all these different things that people are doing with it.

Ravi: That’s right. Something I’ve been thinking about, along these lines is like a, an AI fluency framework. And, um, I can kinda see maybe four different, different categories of, of AI adoption. I think the first being, resistance, which is what we’ve talked about already. You know, the, your first encounter with AI is often.

Uh, well, it’s maybe not often, but often people can be quite skeptical.

Angie: Hmm. I remember the first feature we put in our product was a AI query assist where it would use gen AI to turn your words into a data query. And very super, super powerful ’cause you could create any filter in the world with your imagination and little to none technical skill.

And, I loved it. It was magic, but our tolerance for it, making mistakes when we first started using it was zero. And us on the customer side of the team threw our hands in the end and said, we can’t possibly release this. It doesn’t get it right every time. And nowadays, like you come to expect that that’s the case, it’s like you Google something and the first result is never, not always the perfect result for you.

That’s why. You get a whole list of them. It’s the same kind of thing, like you prompt AI and it gives you an answer and then you have a conversation with it to get to the right answer. That’s both your brain and it’s thinking, and it doesn’t necessarily get it right every time. And I think back to our, our first resistance on our first feature is very much that.

Ravi: Yeah. And I think that’s a story that could be shared by, by many, many, many others, um, all around. And it’s funny because I think, you know, people talk about AI as having like a corpus of the entire world’s knowledge within it, but it’s memory is, is extremely tiny. And understanding how to harness that knowledge with such a small amount of memory is, is quite interesting.

And I think. Initially we struggled to, to really understand what that meant and why we wouldn’t always get the same answer. And it was probabilistic. So I think it’s all part of the, the learning process for us and, and any sort of user and getting

Angie: comfortable with the discomfort of releasing a probabilistic product in the first place.

Ravi: That’s right. Then when I think back, I think the next phase we sort of got to was that, is that through all that excitement, it was like, how can we adopt it everywhere? And, you know, both in terms of business processes using Chat GPT to write and summarize and do all of those great tasks as well as, um, solve a lot of hard, problems building our product.

And then, you know, we, we quickly realize actually. It can’t do all of these things, at least not yet. So there are limitations that I think are important to understand before you can really move to the next level of, of proficiency and efficiency. With ai,

Angie: do you think we’ll see like the sort of, what is it more as law or whatever it is of improvement?

Have I got the right law? It’s definitely not Murphy’s Law. When it comes to the memory problem, like is that something that’s gonna get better exponentially or is that always gonna be a limitation?

Ravi: It’s a great question. I’m not an expert. In order to answer that, I expect that we’re gonna continue to, to improve.

And I mean, we, we know, history tells us that humans are amazing at creating these, these scientific barriers. As soon as we think that we’re about to hit a wall, something new, new opens up. We get past that and, um, I think that’s what we’re gonna see playing out. But I don’t know. I don’t know if we’d ever it’s ever gonna be perfect and I think it comes back to a point of around, I still think there’s a huge amount of value in humans applying critical thought to their use of AI

I think you’re always guaranteed to get a better result. If you are the one who’s, who’s in charge and, and not blindly assuming, what you get out from an AI is correct and, and reasonable.

And so I think there’s still a huge amount of influence that humans have on quality of results. Comes back to how we prompt it, how we review output, and how we use it to build with. I think that’s why you get these, these, sometimes these polarizing takes across the end of the spectrum where some people claim it’s absolute junk and garbage and others.

The best thing since sliced bread,

Angie: I’ve found for myself, there’s kind of two modes of how I use AI in terms of thinking. It’s like there’s some things where I say, just do this, you know, like. Maybe we’ve got a blog post and we need a short description of it to go onto the website. You know, something simple like that.

I can give it a copy, it can generate it to me, I can give it a quick review.

But then there’s other things like preparing for today’s discussion. Mm-hmm. Where I don’t want to just say, we’re gonna record a podcast about this topic. Tell me what I should talk about. Mm-hmm. You know, I wanna say like.

Here’s this topic and here’s my thinking on it and what am I missing and you know, how could I develop this idea better? And sort of these two different modes of like, do this for me versus think with me.

Ravi: Yeah.

Angie: And I think a lot of the times where we are unhappy with the result, it’s ’cause we’ve kind of used the wrong mode and how we’ve approached it.

Ravi: We’re trying to outsource our, the thinking. Yeah. Which I think is an natural thing to do.

Angie: Yeah.

Ravi: Um, that’s right. And it’s, um, it’s something that’s close to my heart as a, as a father of, of kids, the elst being 13, I, I really, really discourage the use of, of AI for them because I think it’s important they understand original thought, what that means and how to.

The process that goes into getting to an answer. Because if they don’t, then how can you judge the quality of what an AI tells you? Which on the surface might, might seem fantastic, but you know, when there’s nuance involved what you’re trying to make, work through a delicate issue.

If you lose that muscle. I think we can all be lulled into the sense of just always accepting what the ai AI says. And, uh, in the engineering, um, team, we’re finding that a lot now we are, we are more likely to steer the AI than let it steer us and drag us around. I think that’s a, a failure mode that we’re at Dexabit

We are definitely trying to, trying to avoid.

Angie: It’s like having a junior engineer, not an equivalent one. Right. I, I think this is interesting that the cases of the, of the kids, you know, you and I grew up in an age where we were the generation after our parents and got the calculator. Mm-hmm. And they all thought that was cheating.

And then sort of probably by the time we were at university, I think it was about around when Google. Came out and the, the internet, you can sort of find information and everybody threw their hands up in the air and said, but what about the libraries? And that was sort of seen as cheating, where these days you wouldn’t conceive of going to university without the internet.

Ravi: Mm-hmm.

Angie: When you’re sort of thinking either about your kids or even about our team and, you know, reading the studies of what generative AI does to the brain. Of the little bit of study that’s been done where it says, was it MIT or something said that it reduced the active pathways in the brain for critical thought.

Mm-hmm. And for students who are using it to write essays versus those that didn’t. And what, what do you worry about when it comes to our use of that and what that does to our brains and what that does to a team or to a child?

Ravi: Well, I’m not sure who to attribute this quote to, but one that I love to describe this is when you go to the, to the gym to do weightlifting, it’s, the purpose is not just to move weights around.

Otherwise you’d, you’d use a forklift, right? I think it’s. I think it’s important to, the brain is not actually a muscle, but I think it’s important to, to treat it like that. Mm-hmm. And encourage those, those pathways because, ‘ cause as I said, I think, although an AI might have the world’s knowledge it doesn’t have the world’s context and it doesn’t have your context or context of the environment you’re operating and really, truly understand the problem that you’re trying to solve.

So I think it’s important that we maintain that critical thought to be able to, to prompt it and, and teach it the values that we care about and why we care about it so that it can draw from the correct pieces of knowledge and, and put it together. Uh, otherwise I think it, it would struggle to, to recognize the patterns that I think.

A sharp human brain can do almost instantly or intuitively to come full circle to this uh, to the topic.

Angie: Mm-hmm. It’s hard to get it to debate you. Well, even if you tell it to be harsh, it’s just, just so agreeable as well.

Ravi: That’s right. It’s, it’s the, it’s the, the, the psycho fantic behavior, which I think all of the, the top providers are, are working on, and it’s quite a challenge because.

Sometimes if you tell it don’t agree with me, it will agree with you to be disagreeable. Yeah, absolutely.

Angie: Right. I shouldn’t agree with you.

Ravi: And almost, and then at least for me, I’m second guessing myself. Is it disagreeing with me because I told it not to agree with me, or is it disagreeing with me?

Because actually there’s a fundamental flaw in my reasoning, and again, I think it’s the, it’s the critical human element that. I think it’s going to be still valued for at least the next few years.

Angie: Is there anything that you do in your work that you feel we shouldn’t use AI for? Like when it comes to creativity or critical thought, is there anything that you purposefully swim in the other direction?

And

Ravi: for me personally, I. I’m not a huge fan of the creative writing that comes out of from AI Not that it’s bad, but I feel like it doesn’t fit the, the, uh, my tone or personality so often. I, I might use it for ideas, but not necessarily to write like pros verbatim, but I am, I’m trying to use it in, in many.

Many more situations. But whether I use the output or not, I think doesn’t really bother me too much, but at least learning about the capabilities and the boundaries of what the AI can do to build up, you know, the intuition. So that next time I have a problem, I, I know actually I can use AI for this, or don’t even think about AI because I’ve tried this in the past.

And I didn’t have good results with it.

Angie: Did we get past resistance?

Ravi: In terms of my suggested AI fluency framework, I think we had resistance and then we were talking about using AI And so that’s, that would be, I think, uh, what I would describe as as point solutions. You’re on chat, GBT, you’re summarizing, you’re writing emails, you’re feeling super productive.

And uh, the recipients are probably inundated with a whole bunch of content thinking, ah, what do I do with all of this? And I think that leads to the next stage. In the, in my AI fluency framework, which is, which is really about adopting a and understanding where does it actually fit best without making my team go crazy, but working together with, with my team.

And I think that’s why I think of it more of like as an organizational level rather than an individual one. That’s one of the things that I think you’ve probably seen is sometimes individuals can go crazy. Because it’s so easy, the cost to generate content is so low. It doesn’t necessarily mean everyone is actually, generating valuable content.

So how do we adopt this really powerful, novel technology without losing sight of the actual objectives or goals that we’re trying to solve?

Angie: What sorts of things have you found works, either like with individuals or with the team in terms of bringing them to that adoption challenge or that adoption nirvana where they’re using it for the right things in the right ways?

In the right direction?

Ravi: In the engineering space because we’re using AI to generate code, we’re able to generate so much, so much more quickly. But that’s putting a whole bunch of pressure on the review process. So as a team, we’ve sort of discussed, got together and discussed potential solutions and how we wanna tackle this, this problem.

And ironically, our solution is really to use more AI Use it to help us with the review process, or even better yet, the design process, so we can, we, we are approaching our work differently in the past because it actually takes a lot of time for a human to implement a solution. We generally do a little bit of upfront planning, pick a path, and then we commit to it and implement it because that was a, there was a lot of work involved.

Taking that same approach as AI just means we, we do things way faster, but we are missing the opportunity of actually trying multiple parts in parallel. And this is, I think, what we’re starting to adopt now. And we are doing it early on in the, in the design process and, and continuously and using multiple ais to review different parts play off.

Off, uh, one and each other. And I think ultimately getting to a higher quality result, a higher quality result than what we would used to be able to do manually and also reduce our review effort because we now know that we’ve been through multiple rounds of AI review, picking edge cases and corner cases, trying out different ideas.

Before it lands, so we are way more confident at that review stage.

Angie: Do you do that using each, using your own ai or do you share an AI between you that’s been trained and sort of has its baseline and training in the same place? Like or do you each have your own flavor?

Ravi: So we all have access to different AI models.

The way we use them is actually quite different. And it comes back to, to what you talked about earlier on, which is around how we prompt an AI And it’s quite interesting because sometimes we are actually independently, uh, using it to come up with ideas and we get different answers as to which direction to go in.

And sometimes it traces back to just really subtle instructions in the prompt, or at least the values that we are sharing as context, which is steering the AI And I think that’s why it’s important for an engineer to be able to think critically to evaluate the merits of the suggested solutions rather than just blindly, uh, accepting what they get.

Or at least you can get a, a much higher quality result if you, if you take that, that step.

Angie: We found that on the customer side, like there are some tasks that we all do that are very similar and quite repetitive.

Ravi: Mm-hmm.

Angie: And so we thought, well, we build a shared GPT and get it customized exactly for these particular tasks as sort of an agent of sorts and all share the same one.

So, for example, we all often create synthetic data for various purposes. Maybe we’ve got a customer who’s moving to a new ticketing vendor and they just wanna kind of get a feel for what the data’s gonna look like, but they don’t have any of their own yet. And so we want that GPT to be informed by what that vendor is.

Data looks like, and that way we can just prompt it with, and this is for, you know, this, this theme park over here, and they’ve got these rides and these tickets and things like this, and create me some data that looks like it belongs to them. But even with a custom GPT that’s been trained centrally, the way that we all prompt it, we get different results and some more frustrating, some more easy, and so much of it becomes quite individual

Ravi: that that’s right.

I think it’s, it’s almost a question of, of art versus science. And when I say art, I can sometimes see some of the engineering work we do. It has similarities because you’ve essentially got an unbounded solution space. So it’s, it’s very much about design. However, there are some tasks which are very, very clear cut in there, more about like, do this thing.

And so for instance, writing queries is a great example because, um, you can sort of prompt it any way you want. There’s a right

Angie: or a wrong way to come up with the answer, huh? Yeah,

Ravi: exactly. And you can be pretty confident you’re gonna get the, the right. Well, an answer that works.

Angie: I must admit we’ve, we’ve had better luck with situations like that, but even still, like, knowing little tricks like, you know, for us, given that none of us are, data engineers ourselves, like little tricks, like knowing in our prompt to, or in the training of the, the custom GPT to make sure it comments almost every line, you know, so that we can read it in English and basic language for ourselves as we are going through to review the, query Doesn’t seem overwhelming.

One of the things that I found quite useful. Almost by mistake is in one-to-ones with some of the team, like actually having almost what’s become an agenda item to kind of talk about the different ways in which they’re using AI in that week and what sort of frustrations they’ve run into, what kind of tips and tricks they’ve picked up on, and sort of share some of that around in addition to the times that we do that together as a team.

Ravi: I’ve definitely done the same with, with my team, and it’s, it’s really great. I, I love hearing about how other people are, are using it and what their learning works for them and we’re starting to build up this collective knowledge around different approaches that we can try and we we’re constantly iterating on that

Angie: organizational intuition.

Ravi: Exactly.

Angie: I notice you haven’t mentioned the word policy. Governance.

Ravi: That’s, that’s right. It’s not my favorite topic, but I think we, uh, we are really great at Dexibit because you know, you and I, I think we, we have this like strong pragmatic view around the technology, what can go wrong and, and how to, how to safeguard our, our staff and our customers.

And I think.

It’s walking a tight trope between being too restrictive that nobody can really get the benefit of it. Or in some instances I’ve, I’ve heard that, um, organizations have provided custom AI models, which are very locked down and very primitive, and they’re, they’re on-prem, but they’re, they’re so far behind that.

People don’t get value from using them. So they, they don’t, well not compared to the, the latest and greatest that you’ll see from, from, um, open AI and anthropic. So it stifles adoption or otherwise generates a lot of poor or maybe suboptimal content. And then I think the other side of this is, if. If you gave everybody free reign, you’d have to be very careful of company and, and customer data.

And so I think the approach that we have taken, which is really to understand the benefit of the technology and to work with it, but amenable to, to our own contracts and policies, um, using company accounts where we can ensure our data isn’t using used for the purposes of training. And complies by our data sovereignty and residency rules that our customers expect from us.

As, as a pragmatic and sensible approach to, to get the benefit of the technology without leaving ourselves open to a large surface area for risk.

Angie: It’s almost having those security foundations and then the right education. For the team of like you started off with knowing when to use what and how.

Mm-hmm. Um, and the rest becomes about almost a trust. Like if, if you’ve got a team member who’s not making the right decisions, they probably don’t have the same context as you, and that becomes a reflection on the issue. Rather than trying to write every scenario onto a policy of a technology, we can’t fully wrap our brains around.

Ravi: Yeah, that’s right. That seems almost futile to me. But I mean, so many organizations are, are spending a lot of blood, sweat, and tears to attempt it

Angie: and time

Ravi: and time

Angie: time’s a race right now.

Ravi: That’s right. And I think it’s, it’s really a struggle because often if. The people who are in charge of writing the policy may not necessarily be the ones who have a deeper understanding of the technology, which makes it even more challenging and even more frustrating for those who are using it at times.

Angie: I think what we’ve seen I’m going to forget who came up with this, but they, uh, saw that. For organizations who didn’t put AI in place for their uses, that their staff were paying for it out of their own pockets and using it on the sly anyway, so there’s almost like a rebellion and it’s gone even further than the sas.

Sort of era where one user in a corner could buy a license and start using something. It’s at the point where you can have it on your own personal phone and start doing something.

Ravi: Exactly. You can take a, a, you can take a photo on your phone and feed it into, into personal AI accounts and, and, and I think that.

That resistance, that approach to put up walls is counterproductive to these organizations because they set themselves up for more risk with individuals putting company data into public accounts that could be used any which way with no, with no traceability.

Angie: I think the reverse is a good way to get people started though.

Ravi: Mm-hmm.

Angie: If you have got a, the right safeguards in place.

Ravi: Mm-hmm.

Angie: Encouraging staff members to use AI for personal means, even if they’re using the work one, as long as you’re not throwing their health records into it or something. But it is quite a, a nice way to get a user underway with AI to get them to do something from their personal life with it, and then they can sort of make the leap into finding opportunities in their work life to use it, which can be slightly less threatening way, especially if you’ve got people who are maybe.

Um, I’m thinking about some of the organizations that we work with where, they’re not technology companies in their own right. So a lot of staff members out there who are still gaining digital confidence.

I am had a family member who had actually worked in. The technology sector most of his life, um, but is now retired.

I won’t name him here, but I was quite surprised that he hadn’t leapt into using generative AI He’s normally quite an explorative person but he likes cooking and he had borrowed a cookbook from the library that he really liked. So I took a photo of one of the recipes that he was interested in and showed him, uploading it to chat GBT and said, you know, write me this recipe out.

’cause he was asking me, oh, can you scan this? And in, of course, a couple of seconds if we had a nice recipe. And then I asked it, oh, could you make it gluten free? Mm. And it just blew his mind. But it was the spark that he needed to dive into it. And I think, you know, if you’ve got users and you’re training them, you know, and educating them and introducing them to AI you know, using some personal.

Little things like that can sort of draw them into this world and ignite that spark of imagination in them, of how they might use it at work.

Ravi: That’s right. I can think back to my personal life. For my wife, it was actually, travel planning. Uh, we. Going on holiday and, uh, to a new city and used a tune of AI to help build together an itinerary as something that we have been thinking a lot about here at Dexibit.

Angie: Oh yes,

Ravi: exactly. Just a whole different podcast altogether. But it was, it was exactly, uh, that you just need to find a little opening in, in everyday life, and you can start to see how powerful the technology’s gonna be.

Angie: Every year, I, um, got as a bunch of conferences for visitor attractions and often, sometimes specifically to the digital space or there’s always a bunch of presentations around the digital space no matter what the format. And over the past nearly 10 years. Like there is always this plethora of app presentations and then there was the blockchain stuff and the more recently the metaverse stuff.

And it, it does tend to give you an eye roll with some of these things, but the gut would say this is different, right?

Ravi: Well, I think so. I, I think it’s easy to be. To hand wave away. AI is just another one of these phases that they were sort of going through. And we’ve sort of seen this with, with a blockchain where a few years ago, uh, it was, it was everything to everyone, but in the end it’s actually really nothing to, to most people.

But I think AI is, is, is very different. And I think you’ve sort of touched on it. What, what, for me personally, makes it different is the way I’ve seen it touch people’s lives personally. And I think no other technology has done that since the, since the smartphone. I think we’re going through this, this phase when people tend to overestimate the effect of a technology in the short term, but we underestimate it in the long term.

So, although it’s hot and hyped right now that doesn’t necessarily mean it’s going to go away, but it’s probably just that catalyst of this slow burn of it becoming more and more omnipresent in both our personal lives and our work lives. So it’s one that I definitely would encourage you not to ignore.

If you’re listening,

Angie: The red sky is the sailors delight then!

Ravi: It is… 

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Hey, Pierre.

Pierre: Hello Angie.

Angie: How’s it going?

Pierre: It is going well. Thank you. How are you? You just came back from holiday, so I guess you’re a lot refresh on a lot of us right now at this time of year,

Angie: the tan at least. I’m just back in from the Cook Islands. It was magical.

Pierre: Oh, nice. We are really jealous.

Everyone is jealous. We are just not telling you.

Angie: You definitely know the Cook Islands better than I. I need to go to outtake next time.

Pierre: It’s, it’s absolutely one of my favorite place on Earth. Absolutely. How was it?

Angie: It’s funny, I was thinking about it. We, we actually planned our entire trip on chat gpt right down to like, what are we, where are we gonna eat today?

What are we gonna do today? It’s raining and we’ve got a toddler running around, you know, what are you doing? Cook Islands time and that kind of weather. And, even selecting our hotel in the first place, my first AI powered holiday.

Pierre: How did it turn out?

Angie: It’s actually pretty good. We ate our way around the islands at the most incredible, places that just had the best experiences and sometimes they weren’t always like the most expensive place, or, you know, the most well known place.

We turned up at a couple where there were sort of, you know, climbing over chickens on the floor and things. and it was just incredible. It’s, it’s a pretty good travel planner.

Pierre: That’s amazing. That’s amazing. I think we’re all using it a little bit more. You know, for, for different reasons. I, I usually.

Use it use charge GPT or other AI tools quite a bit when it comes to purchasing something and making sure I compare the products in, in a very transparent way. ’cause you can, you know, you can use different sources, right? And, and compare the, the criteria and stuff. But yeah, I think like people are increasingly using it for.

Planning either, you know, financial planning, holiday planning as you, as you mentioned, and I think it’s just gonna get even more and more and more common. Right?

Angie: Yeah. You might hear in my voice, I lost my voice. Coming back from the Cook Islands and I’m, I must admit, to cheating at parenting.

And I put it on voice mode and asked it to come up with a, a story about my little boy being Superman or Batman and his best mate being Robin. And, and saved myself a car right home of having to talk ’cause I had no voice left. So, uh, there’s a, there’s a chat, deputy t use case for everything.

Pierre: I feel like the chat GPT skis 10.0 nj.

That’s brilliant.

Angie: I was having to get creative, but it sounds like a few of our visitors out there in the attractions industry are getting creative too.

Pierre: Yeah, absolutely. I think, you know, just like what you did with your travel, right? There’s an increasing number of, users just asking, you know, questions to the systems.

You know, I’m in a city for X amount of hours or X amount of days. What are the most two, what should I be seeing, when should I be seeing it? and then they, so they either would be using chat, you know, chat, GPT, cloud, et cetera, to, to do so, or they may be asking Google and. You know, as you’re aware, we now have AI generated answers in Google where people don’t need to click on links anymore, and they just got the answer straight in front of them without having to dig.

 for, for answers. So taking away that extra step of clicking on, on websites, on sources. so yeah, I think, I think definitely an increasing pattern for sure.

Angie: We’re seeing a couple of data points actually on this. the first is that the Google Analytics results for a lot of places are all over the place.

And I think, We are certainly entering an age where we’re gonna watch these probably decline, because people no longer need to actually physically come and click on your website. And also there’s a lot of stuff going along in, cookie land that are changing the landscape there. And the second is that we’re seeing, where we’ve got attractions who do visitor evaluation, they exit, um, intercept surveys and they ask their visitors, you know, how did your visit go today? And maybe, , who did you come with? Or any of the other sort of questions that they can’t pick up through, quantitative data. One of the questions they commonly are asking now is, um, did you use.

Generative AI in planning your visit here today. And at surprisingly large, an increasing, dramatically increasing number of visitors are saying yes and. It surprises me how big that, that figure is for many places and how quickly it’s growing. It’s certainly outdone a lot of my expectations. So I think just seeing just how aggressive that is.

This is going to be one of the defining trends of the coming year.

Pierre: I like what you said and I think there was, um, you know, there’s an element of of convenience as well, right. You know, you’ll have your traditional AI users that may only have it on their desktop, et cetera. And then you have like the advanced people that probably have it on their smartphone as well.

And you can actually request on the go right, as well. And that, I think that’s gonna be a lot more common, right, of like impromptu requests of be like, I’m here right now, what should I be doing? Are there any events in the area? Et cetera, et cetera. And maybe you know that, that, that’s kinda.

That’s gonna influence behavior for visitation as well.

Angie: Possibly even on site, like I’m here at the Louv, where am I going? You know, true. What should I do? Yeah, it’s a really interesting thing. And, and like you mentioned with the, the Google results, um, I even wonder whether that figure that we’re seeing on those visitor evaluation surveys is actually undershooting because for a lot of visitors, they might be using the Google search, still getting a generative ai.

Reply within their Google search result, not realizing that that’s what it is. Um, and therefore not self-reporting and that they’re using AI and planning. So, yeah, it’s, it’s possibly even a larger number of visitors than we think.

Pierre: You’re totally right and I feel like, you know, um. When that, how did you hear about this question?

Is, is really tricky and I guess the numbers I usually you know to take with a grain of salt I guess. ’cause people want to be helpful and they want to tell you how they think they heard about you. But as you mentioned, it may be coming from a source and they think it’s coming from somewhere, but it’s actually coming from from somewhere different.

When I used to work for, uh, the largest food, restaurant aggregator in the world, in my. In my past, we, we had this quite often, right? How did you hear about us? And funny enough, they were coming on our website, but their first answer was Google because they googled the name of the restaurant and they actually landed on our website, where they had all the information to make a booking, et cetera, to all the takeaway.

So I think that that will be happening right now. You’re right, like people searching, getting an answer of the ai and potentially. Giving you a friendly mislead on how they heard about you maybe, and maybe undershooting that figure for quite a bit.

Angie: Yeah. Thank you. That’s such a, actually a really actionable first, first point off the, um, first cab off the rank for, for today’s episode is if you have a, how do you, how did you hear about us option, say when a visitor books a ticket and AI isn’t on your dropdown list, if it is one.

Let’s get it on there pretty quick. Smart. Um, likewise, if you’ve got visitor intercept surveys running and you haven’t got a question in there about did you use AI as part of your, trip plan or your visit plan, um, let’s get that question in there pretty quick as well. And these are, are two really quickly progressing.

Uh, things that we can do just to get a, a harness of, what our visitors are up to.

Pierre: Yeah, 100%. And there’s a way you can shake how you’re performing. Tell us a little bit about, about that and how you know, how appealing you can be to AI when people are searching.

Angie: Oh, yes. And so I think that this, this area is going to become the defining thing for growth, um, over the coming weeks, months, years, and particularly.

If I’m to put my money on something, I think it’s gonna be by the end of this year. Um, a visitor might be able to actually book a ticket via chat, GBT. Currently you can’t. So currently I can do all my planning, but I still leap over to the website if I want to make an advance reservation somewhere, whether that’s at a restaurant or a uh, as you mentioned, or a attraction or an airline or a hotel or whatever.

But my prediction would be. By November, December, we’ll see at least some of, of the gen ai platforms actually go as far as making bookings. And so it, we will very quickly get to a point where a visitor may not get to your website, even if they’re doing an advanced pass. They’re just wholly interacting with, with AI as part of their visit plan.

So what we’ve done at Dexibit One of the frustrations we have is that these Gen AI platforms don’t currently release any data on them. So like we can get outta Google Analytics to see, you know, how many people visit your website and even out of Google search to see, um, what the different search terms are and things.

We don’t currently have any, any visibility as to what’s happening inside those conversations. So we thought we’d change that. And first of all give visitor attractions an assessment tool to understand what exactly chat-gpt and the likes are saying about them, how well they’re, how visible they are.

And then also. Beyond that to be able to compare themselves to their peers and really use this as a competitive differentiation, positioning, um, performance tool not only for marketers, but for everybody involved in the visitor experience in very various aspects. And so. We have launched a new GEO.

We are calling it Benchmark. so this is sort of the a nod to the SEO world of search engine optimization. This is generative engine optimization, to make sure that for your attraction, um, it’s getting mentioned in generative ai. It’s getting positive sentiment in terms of how that mentioned is

Done, that that description is accurate, um, and how you’d want to be represented and that your things like what questions visitors are asking and things are all optimized to make sure that you are getting the most out of this as possible. So it’s a super, super novel, exciting, very innovative.

Uh, look at the world, and I think this is gonna be a really fascinating data set to get deeper and deeper into.

Pierre: Now you’ve mentioned GEO, right? Like generative engine optimization. Is that, is that like a term that’s widely used right now you think? Or is that a term that’s currently internally used for us to refer, to?

Refer, sorry, to, to that specific aspect of, of generative ai.

Angie: I’m not sure sure who or where this was coined. It is definitely when we’ve picked up breath and invented ourselves. Uh, so we won’t take the credit for that. But, um, yeah, definitely this is becoming like the, the marketing frontier for, for marketing teams to get into.

So, definitely very, very topical for anybody who’s in the growth space.

Pierre: I love that for listeners here. So if they hear that term again right there, let’s give them a little bit of, of context of what it is. So GEO, generative engine optimization. Love it.

Angie: Yeah. So what we have done though is we’ve developed a couple of things.

The first is a GEO rank. So how do you do, how do you do in comparison to peers in terms of your mention ability on generative ai? So for example, how often are you mentioned when people talk about coming to visit your city or your country, or when they talk about your category and, as you, you mentioned it actually at the beginning of this, um, you gave an example of you know, I’m heading to this city in such and such a time and I wanna do such and such a thing.

And I actually found myself when I’m wandering around the Cook Islands doing exactly the same thing, with generative ai, it’s like, you know, we’ve had far too much fish and seafood and we want, um, a dirty old hamburger for dinner and, but I’ve got a toddler so I don’t wanna go anywhere fancy. You know, it’s gotta be somewhere where he can run around and go crazy.

 and it’s our last nights we want it to be kind of iconic, you know, like it’s a really involved sort of personalized recommendation conversation. And so when we think about like. It’s not just as simple as saying like, top things to do in America. You know, it’s like very, very specific in terms of how potential visitors might define what their interests are in and how that mention might come up in that conversation.

So that’s really interesting. So. This GEO rank, um, sort of looks at how you perform in that mention ability and how that performs relative to your peers in those, those areas. And then we sort of get, dig into like, and what’s the sentiment of that mention? Is it positive, is it negative? What’s the family friendliness of that and what’s the accessibility? And so we sort of look at all of these different dimensions of not just how frequently that mention is, but how favorable it is. And we also look at things like the sort of questions that visitors are asking and how

your attraction is described and what the keywords are. And so we form all of this into a GEO profile. And so you can then sort of look at how your overall score of performance and generative AI is fairing. So that’s how we’ve built out this assessment tool and how the benchmark is formed. and then it sort of dives into all of these different areas.

So it’s a really, really fascinating piece of data.

Pierre: I like that and I, I wonder, my mind is going, slightly sideways. And it’s, it’s wondering if that score, that ranking or, you know, how often users will be using these models are influenced by the destination that they’re going. So, you know, in my mind, if it’s a really well known destination, they’ll already know what are the must dos.

And if it’s not really a really well known destinations, maybe they will be using this. Tools a little bit more heavily. So I wonder, you know, my mind is, is going there as well. It’s like, I wonder if there is a, a difference here and then if there is a, this difference in the ranking, um, between attractions in these different places, right?

So top attraction in a destination that’s not well known versus a top attraction. You know, a, a destination that’s a really well known destination. But that’s really useful.

Angie: Yeah, certainly actually the, the well-known attractions feature really well, probably because they’re talked about a lot. And so for example, if I’m going to New York, of course the Met and MoMA are gonna be up on the list of, um, and score really well and some of the more boutique places off the beaten path, maybe outside of Manhattan aren’t going to fear so well.

But, There’s also ones that are notably absent. there’s high performing niche niche places that make a great appearance elsewhere. And likewise some that aren’t. There’s, there’s definitely a skew towards quite a positive feel. So, the likes of char-gpt tend to be quite, quite kind in the way that they describe a lot of these attractions and very delicate about how they mention some of their shortcomings.

Um, but we have found overall. That the GEO score is better, where the overall sentiment is better. So, what that means is that attractions that are perceived to be more beloved, are more visible. With with generative ai, it tends to favor things that people love and, and places that have a genuinely great visitor experience.

And we can see that in the correlations too between high quality experiences with generative visibility. And that’s probably because things like word of mouth and reviews and user feedback and things are, influencing the AI’s training data. Then we can see as well that the same is true to a slightly lesser degree for family friendliness and accessibility actually on, on equal power with each other.

They, you know, scoring well for families reflecting inclusive design. We are, both of those audiences are served that tends to, to serve their geo visibility as well. So those are, those are sort of, the interesting points and I think, what this says to me is that the voice of the visitor is now no longer an afterthought.

You know, it’s no longer a lagging indicator of like how well you’re doing that. If somebody walks out the door, you could say, oh, did you have a good time? This is now a growth input, like this is now how your visitors are enjoying their visit, how they talk about that, that voice of their feedback is now starting to dictate how well you do in the market, and it’s just become far more important than ever.

Pierre: That is so interesting. I mean, yeah, you’re right. It’s, it’s coming from you know, call it reactive place to actually a very proactive place, as in we need to have. Good feedback because it’s gonna impact this, this, and this. On, on that, you know, on these models. So you spoke about visitor feedback, right?

Mainly online. So via Google, you know, the other review agreement, Reddit, what?

Angie: Yeah, Reddit. Reddi Design a really popular place. Yeah,

Pierre: yeah, yeah, for sure. What about the reply. Of the management of that institution. Does this have an impact on that score alone?

Angie: Bingo. Um, I’ve heard you say this to so many customers, you, you’ll have to repeat it for all the other listeners who haven’t heard you say this before.

Pierre: What, what do I usually say? I say so many things

Angie: about how important it is to reply to your Google reviews.

Pierre: Absolutely. I think, You know, it’s coming from, again, my experience in, in reviews and, and all that, but also there’s a there’s a concept in philosophy that’s defined the self, and I think I’ve mentioned that before, but for the people that did not listen to the previous episodes, I repeat myself.

But self is, is a combination of two things, right? Self is a combination of how you think about yourself. And how you think you are. And then it’s also a a factor of how people perceive you and the true self. So your true self is actually in the middle, right? Because it’s a mix of how people see you, and it’s a mix of how you see yourself.

And that review is exactly the same thing. There is an aspect of how people give you feedback and perceive the experience, and then there is an aspect of how, um, you can reply to that and give your point of view of, oh, you know, we appreciate your feedback on this and we are trying to do this, or this is what we’re trying to narrate, et cetera, et cetera.

So I like that and that’s why it’s important to reply to reviews, but you’re telling us now it’s even more important to reply to reviews. Because it will have, um, you know, will be a, an input for performance on the marketing side, essentially.

Angie: Yeah. That training data covers both what they said and what you said.

I feel like we just went really deep on the self. Um,

 I need some, some the, to peel back that layer of the onion and. But yeah, absolutely it is both. It’s hard to tell, you know, how much waiting goes which way? When it comes to gen AI’s training, but both. Are important. And funnily enough, one of the aspects that is important is like the emotion of it and the enthusiasm of it.

And one of the things that we’ve seen in the data, interestingly enough, is that maybe there’s a little bit of bias towards sort of American lens, cultural lens on the world. And what I mean by this is that a visitor to like a British. Attraction can go along and say, oh, it wasn’t bad. And what they mean by that is they had a great time, but equally, you know, an American can go along to an American attraction and say it was just the best.

You know, I had the time of my life and they’re actually probably saying the same thing. In terms of once you take sort of cultural context out of it. But AI seems to bias that emotion and that enthusiasm. And so one of the things you can do is ramp up that emotional response in your reply, and bring some of that rah rah spirit into your, review content for one of a better word through how you respond to it.

And also you can sort of, you know, you can. Kind of interpret how visitors are saying something. So for example, a common thing might be for a visitor to say it was really noisy. There were lots of children running around. Like, don’t necessarily reply to that to be assuming that that’s a bad thing.

You know, you could, you could reply to that and say, we love the atmosphere that the kids create in our attraction. You know, and immediately you’re sort of, you know, not only. Putting a positive spin on that for that visitor and any other visitor who’s reading this review. But, you know, giving that ai, that positive spin, that’s gonna help with this training data as well.

So, I think it’s a really curious thing that that emotion of the visitor voice is playing a really big role.

Pierre: I feel like there will be a, a nuance to that, right? Like if you had a review. That was saying the food at the cafe was really bad because my bone bread was stale. And you reply, yes, we all about recycling.

Okay. There’s so, you know, may, maybe there’s a, there’s a limit, right? That you can push. But I, I, I do like the fact that you say you know, essentially if you have a, you. Talk about, you know, a European, let’s take the French. ’cause we’re usually very heavy on the, on the negative feedback.

Sometimes if a French person was like, it wasn’t bad, what you will reply would be, we are glad that you had the time of your life at the museum. Please come back essentially, right. Is that what you’re saying?

Angie: Yeah. And maybe like, double click on some of the things that your visitors are saying. Go deep in them as well.

So not just putting the roast tinted glasses on about the, the bad bread, but you know, offer a bit more information each time you reply rather than just, you know, glad you had a great time. I love that. Um, because again, that’s creating more and more content, which is really interesting as well. So, one of the things that we have put into this benchmark data and the assessment data, um, that you get on your own attraction as well as what you can see on the wider industry is a couple of.

Things. And they are the primary persona of the users or, or visitors that are commonly conversing with AI about your attraction. And, not to say that this is an exhaustive, um, persona or avatar, but just that this is like a common, example primary persona. We can also see what their motivations are.

Um, so, in the way that we’ve created this data set, you can see that this is like a theater goer and their name is Lanar and they’re interested in cultural performances about X, y, Z, for example. And, so it gives you a team, sort of an an example person of who might be, um, engaging with. AI about their visit.

And the other thing that we’ve added into there is a missed market persona and a justification of why that market is missing, and also some suggestions around how you can go about creating content for that missed market. And this comes back to your point that you made originally. Which is that we start to get super specific when we have these conversations with ai.

And it’s not just what can I do in New York, but it’s like I’m a, I’m a student and it’s always been my life dream to come to New York and I’m doing it for the first time and I wanna have a really iconic experience. And I’ve been watching this movie and. You know, what can I do? And so it’s by using these kind of personas in mind that we can start to create content, um, whether it’s in the replies to our reviews, or whether it’s, um, blogs that we put on our website or, whether it’s.

Influencers that we get to cover our, our visitor attraction and put their content out in the world and their platforms, to start to appeal to some of these more niche audiences. And, and rather than sort of treat every visitor as the same vanilla, we start to get all the different flavors coming through.

And we’ve often talked in the attraction sector about like hyper-personalization and never really got there, you know, all the apps in the world have tried, but this is kind of it like. The visitors are doing it for themselves, so to speak. And how we deliver on this through content and, and how we take this time to sort of inject this stuff everywhere in the training data that, that AI picks up, um, as part of, of supporting that hyper-personalization.

Pierre: I love that. So there’s probably like a few. Do you say like practical, tactical, actionable stuff that you need to do if you wanna, if you wanna win at the game, essentially the new game, right?

Angie: Yeah. Yeah. So in, in the example of like the theater, go Elena, you know, like I would put a, something up on my website about, how such and such a type of theater interest is, you know, and this is what they should visit during their visit, um, to the attraction.

Or these are the particular event schedules or public program or things that they might enjoy. Or maybe it’s like an architect’s architect lovers visit and sort of features of the building that they should look out for or. Maybe they’re a botanist enthusiast and, you know, talk about the different plants that are on the property.

Who knows? Um, but I would get some of this content out there in whichever form you can. Put it into your blog post, put it into your YouTube, and do a little walking tour, you know, however it gets out there into the world. And the other thing that I pick up on is FAQs. If you don’t have an FAQ section on your website, get one up there.

Quick, smart. And the, a great place to start is in this section with the GEO assessment tool. There is frequently asked questions by users with generative AI who are thinking about visiting or attraction. What do they ask? And weirdly, some of these might not be things that you have thought about.

Like a lot of them are around sort of, Can I bring children of this age? Is it suitable for children of this age? You know, these are sorts of things that you can, first of all have a FAQ section to answer a whole pile of them, and then like, dig deeper on each one and maybe do, again, a blog post or something similar about that particular.

Question and go deep on it. Like, yes, you can bring children under five. Here’s what we would do, you know, things to do with them. Here’s things to pack, here’s what to consider, here’s where the change rooms are. You know, all of these sorts of things. And that will help when gen AI is having those conversations with your visitor.

Get that mention in there and get that content, in there as well.

Pierre: No, I love that. I love that. And I think like there is a few scenarios where that would work, right? Like low sensory tools you know, like we talked about like accessibility earlier, so like wheelchair, prem, et cetera, et cetera. There’d be a lot of, um, situations where they’ll apply Now.

It may be a lot to take in. Right now it’s a new topic. There’s a lot of stuff that you can do. If you were to start from scratch, like what will be like the three or four things that you’ll, you’ll do like in order of importance you think,

Angie: oh, to, to optimize for gen and gene AI overall.

Pierre: Yes.

Angie: Ooh. Well, I mean, SEO is not dead.

So your original search engine optimization to make sure, say for example, that you rank well in Google is still relevant in a gen AI world because it’s gotta find you to begin with. so I would still keep investing in that. Like, don’t stop. The second one is I would get some of that content up, start with the FAQs, and then the third one is, as we, mentioned at the beginning, is like, get some data around to what degree these visitors are are using this already and maybe some feedback with them or maybe go deeper on some of that evaluation if you’ve got the opportunity too, to ask them about those conversations and just sort of learn through observation about how your visitors are using gene ai.

And one of my favorite things actually that’s in the assessment tool is it gives you your comparative twin. So this is an attraction around the world that it finds most like you in many different ways and aspects of the conversations that it has with your visitors. And so I would look at them and say.

Well, what do you know if their, if their scores are better than your scores? It’s a benchmark so you can see them. If their scores are better than your scores, what do they do that I don’t like? Or what do their visitors ask them about them? versus how does that compare to my visitor FAQs, you know, how they describe versus me.

And what about their visitor experience notes and that my accessibility notes, like how do all of these sorts of things compare and use them as an example, and then maybe do the same with like your. Neighbors and your peers and other sort of like venues that you would compare to yourself as well.

And sort of just, you know, help yourself to that benchmark data to be able to do some competitive positioning and differentiation and start to sort of borrow from others and make some initial first leaps with your your profiling.

Pierre: Nice. These benchmarks are available right now, right? We’ve been looking at it for a few weeks already.

We’ve been digging into it for a few weeks. So if folks wanna, wanna find out a little bit more about that, it is in Dexibit right now. Don’t be shy. Ask. Ask, right? Ask. And we’ll, we will show you essentially, and there’s, there’s a lot of interesting stuff happening, I think on that benchmark.

Angie: Yeah.

And fascinating. And I’m just, yeah, I’m just so thrilled to have some data to, to look at when it comes to Gen ai. So Sick of the Black Box. Hopefully they come out with some metrics fairly soon.

Pierre: Fair one. Hopefully

Angie: I might go and start planning my next vacation in the Cook Islands, Pierre. Maybe by this time I’ll be booking my flights all through chat

Pierre: I would be really interested to see how that, that user you know, experience goes, I think like you just start a, a cart, right? And, and confirm your card at the end, I guess. And they’d be like, you have these tickets and you have this hotel and you have these activities planned out. Confirm your cart.

Yes, there you go. You’re off in two weeks.

Angie: It’s gonna be a fascinating ride. And definitely a challenge for everybody out there in the ticketing world. You know, this is, this is gonna be the new normal gone as the user interface.

Pierre: True.

Angie: Well, on that note, have a fabulous weekend, Pierre. I’m off to go and do some research on that vacation.

Pierre: Thanks, Angie. Until next time!

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Hey, Pierre How’s it going?

Pierre: We are good. How are you?

Angie: Good, good. Talking all about new build visitor attractions today. We had to hit the record button on this podcast in a hurry because we were so excited talking about this topic. We got half underway before we even started.

Pierre: I love that. It is a topic that we really like here at the Dexibit and. And we see more and more new venues popping up, right? And, and joining us, which is really exciting, and they all have a different story. So we, maybe we can talk a little bit about all the different stories that we’ve seen so far, the ups and downs, the challenges, the big wins, et cetera, et.

Angie: I mean, there’s some huge projects happening around the world and visitor attractions at the moment. The V&A in London, of course, opening the East Storehouse and the whole Maritime City project over there as well. Wales have got a new national museum on the way. In New York, there’s been like the Frick with their reopening new museum, doing a double of their gallery space and Studio Museum in Harlem.

And then around the US and the world, lots of new attractions opening up from nail Shima and Japan through to the Museum of Migration in the Netherlands. I mean, it is just we’re spoiled for choice at the moment with new openings.

Pierre: We are spoilt for choice. And I think that’s one of the first things that we’ll talk about, right, is how competitive a landscape can be. Who should you consider your competitors? What are. They doing, how much they’re charging, et cetera. So you can understand a little bit more about, you know, the landscape that you will evolve on once your attraction is open.

Angie: And we were, we were talking about just before we hit record about the two different types of, new visitor attraction teams as well. We tend to see two quite distinct passions is there is the new builds where they’re part of actually a larger parent organization who is, involved in a different activity.

Often they’re not in the business of running a visitor attraction. Maybe they’re a nonprofit, maybe they’re a commercial entity, and they’ve decided to get into the business of, opening a new visitor attraction. So they, they’ve got like this startup team within this really large corporate enterprise. And then there’s the other kind of pattern where you’ve got a pure, true startup where this is all and everything they do and they’re doing it for the first time and there’s no parent looking over the shoulder.

And they do truly have that, that nice startup culture amongst them. Two quite different teams.

Pierre: Yeah, absolutely. I think by nature one will be more rapid and agile than the other one. Right. But essentially very, very different way of, of treading. Also being part of a big corporation doesn’t necessarily mean a well oiled machine for a specific industry, as you mentioned. Right. If someone is not. From this industry they may have processes in place and these processes may or may not fit our specific industry. And unfortunately you have to be pragmatic and, and start to realize that. And it’s a game of how quickly you can realize what processes are fitting or not fitting that specific industry that we evolve in.

Angie: It’s almost a burden, isn’t it? If you’re part of a larger parent organization, but that parent organization doesn’t do what you do and you are trying to act like a startup and you need to act like a startup, but you are bound by. All the heavy burdens that they bring along with them. It’s a really hard space to be.

I think what we see is that typically before opening money and time, feel really abundant to those teams and, that sort of feeling and their culture starts to add in lots of layers and complexity and often slows them down and makes things more expensive for them. And then after opening their team’s ability to sort of survive the robustness of embracing failure of the series of learning opportunities towards a success that’s inevitable for any startup as it puts its offering out in the world.

It’s quite dampened in that corporate environment.

Pierre: And things take time, right? The more complex an organization is, the more layered. You’re gonna have and you’ve mentioned earlier that in some instances, these large organizations have like a specific team that will have full ownership of that project. But in some other instances, this specific team will have to report to another team that will then make decisions or go through you know, a change approval.

And that takes time. And you and I know that. In this industry you need to react very quickly on specific matters for you to be able to repair any mistakes or anything that is not performing as it should be to be able to um, you know, to make that right very quickly. And it’s, it’s really important, right, when you’re facing the public to make sure that you are fixing the small mistakes very quickly.

Angie: Yeah. Thank you. Like that, that point about agility. It’s so important for any attraction. To be able to respond to what they’re saying and take action fast. But for that new build, especially in those first few days and weeks, they need full autonomy if they don’t already have it.

Pierre: Absolutely. And, you know, it can be very simple very simple tasks such as are our opening hours, right. Are we maximizing our opening time based on visitor behaviors and, and what people are doing around the city, for example. And you know, you may find when we talk about large organizations, so we spoke about larger organizations that. Where visitor attraction is not the core business, but you may have a case or a few cases where elicit core business and they’re, you know, branching out to a new city, to a new country. You also need to understand the behaviors of people in that specific country, right. For things such as your opening time, right?

We know that we are very, very different. There are very different behaviors across the world when people are visiting at peak times. You know, when when people are coming and what days of the week they’re coming, et cetera, et cetera. So it’s, it’s really important to have that agility on that path, right?

You, you want to, you want to tailor that very quickly.

Angie: Yeah, you can. I think you can get sort of fooled into the trap of thinking that. A new build is the journey to opening and really the opening is the the start line, and it’s at that point you run your series of experiments to see whether your ideas and assumptions hold true and how the market responds and learn as you go.

And you’ve gotta be able to test out everything and then decide to pivot or persevere at that point and keep that agility. Come from a place where you assume that most of your ideas probably won’t work. And and start from there, whether that’s those ticket prices or those opening times or whatever the case might be, conversion rates and so forth.

And I think a lot of a lot of new build teams sort of assume that they’re leading up to a point of, of doneness and completeness and maybe it’ll be more a period of refinement rather than anticipating that it’ll be quite, quite some wholesale change in those early weeks and months.

Pierre: Yeah, 100%. And I, I think you’re right in term of. You know, assumption, right? That you, you do market research, right? You do your target demographic, visitor demon, you do your competitor analysis, et cetera, et cetera. You’re benchmarking whatever it is that you need to do. Obviously you’re gonna do a lot of homework, but you are still making a few assumptions, right? And, and before we start, I think uh, you know, I was mentioning something to you like as a person by default, I do like simple things, right? But I think in this case it’s also true is that it’s, it’s always easier to start simple and hit the, you know, hit the basics right and build up on these basics based on trends and insights that you see.

Once the attraction is open, then. Really doing a lot of you know, customization and offering different packages and different experience and, you know, different memberships from the get go. And then potentially hit the mark. And the reason why I’m saying that is it’s always gonna be quicker. To build the reputation up than to actually salvage a reputation that you may damage from the get go.

The world spreads quickly, right? If it’s good enough, people are gonna talk about it. If they did not have a good experience, they’re also gonna talk about it, and they are likely to be more vocal about that. And then again, it’s a matter of reacting to that, but it’s a lot harder to react to you know, either a neutral or negative first experience.

Anige: Yeah, that’s so true and, and we have this idea in startup land of the minimum viable product or the MVP, and I think that this kind of tracks into your idea of keeping things simple from the get go and then like developing what’s great. And this is this, this idea that when you’re testing something out in the market and it, it is hard to sort of brand a new builds attraction as a test because there’s so much investment going into it.

You want it to be right, but it is essentially that it’s something completely unproven full of assumptions known and unknown. But this MVP idea is that you sort of put across the, the smallest version, you know, the skateboard rather than the Maserati of your solution to what people want or your, your product of what people want.

And then you iterate on that to build on it. And I think like you say, whether it’s like the ticketing structure or the value proposition to the visitor, or even like the. The retail strategy, merchandising strategy, like just keep that super, super simple to get across the line and then add in the complexity and the layers and everything else later on once you can start to see what works and what doesn’t, because reducing that time until open day, reducing the cost investment until that point.

Means that you don’t get on the other side of that and go, oh, this doesn’t work. And then you’ve sort of sunk all of that time and and investment and, and complexity and, and building things that people don’t want.

Pierre: Yeah, it’s, it’s so true. I think pricing will play a big part of that, right? Like pricing it correctly from the get go. And this is where like, I mean, personally here, my take will be that. You will never upset someone if you price slightly lower than anything else in the market because what are you trained to do right now when you open is likely grabbing market share from someone else. And if you want to grab market share from someone else, yeah, you’re on the new kid on the block, it’s great. You are a new experience. But also if it’s priced attractively, you’re gonna attract people. The early people that are gonna come you know, come to your attraction, they’re likely gonna. they’re likely gonna rave about you, et cetera.

But if you price it attractively, you’re increasing that behavior, increasing that excitement or be like, whoa, it’s new attraction. It’s. Either a little bit cheaper than everything that’s around, or the same price, but I feel like sometimes people try to be a little bit too, how would we call it? Too hungry in term of the pricing and the pricing you know, fairly on the, on the high side because there’s a new attraction and it’s always easier to increase your price later on. And to actually advertise that your price have changed because your thought was, you know, because you bring your price down ’cause it was too expensive at the start. So my take will be that, right? You’re trying to grab market share and be competitive from the get go and then you can adjust instead of trying to go best case scenario into want to make X amount of money from the start. That would be my take on that.

Angie: Yeah, I have mixed feelings about pricing and pricing strategy. I think most visitor attractions. Under price themselves and they’ve got a bit more flexibility and elasticity in their price than they anticipate. And I do think without getting into the realm where you come in so hot and you’re pricing that you develop this perception in the market that you are expensive in that lives with you forever in a day is your reputation.

If you can be on the higher side. Relative to your competitors, but not out of the water. I don’t think that that would be a, a bad thing. I wouldn’t necessarily, if it were me fully undercut everyone as a entry point. And there’s kind of two ways to play that around opening. I think there’s sort of the price it and then discount it to say it’s like opening special.

Or make use of the sort of novelty and demand and limited capacity of opening to have that opening price and then maybe discount it later on as you, as you need to. But yeah, it’s such a tricky one and so market specific as well. On what, yeah, what the price points of your competitors are and how competitive that market is, and whether you are unique, whether you are novel, whether you are high value or not.

But yeah, definitely seen a couple of options where, new builds weren’t clear about the fact that they were gonna price and the public’s perception in their city thought that they were gonna be free and got hit with that PR message really late in the piece, that it was gonna be a paid experience.

And the other sort of mistake that I’ve seen is. Just like absurd pricing expectations that are just far, you know, double what’s on the market for what they are. And I think you gotta sort of translate that into some industry norms like. Cost per minute of visit and compare that to your attraction.

Particularly if you aren’t going to be somewhere that people are spending a long period of time, like, don’t then price yourself similar to experiences where they spend double the the time that they’re going to spend with you. There’s sort of a general tolerance of what people will, will pay per minute for something that might take them an hour to go through or something.

And and then also sort of thinking about that relative to the audience. Like is it child centric or adult centric, and how are you pricing? Who the experience is valuable for you know, if you are a child targeted experience and the adult ticket price is really expensive and that can then, hit hard as well.

Pierre: What, what’s your thought on, you know, when we talk pricing and, and ticket, what’s your what’s your thinking around, you know, partnering with. Like third party agents to, to sell tickets on your behalf or to offer tickets on, on your behalf from the get go, what do you think? I haven’t made up my mind on that yet for new attraction, but I’m keen to hear your thoughts.

Angie: Yeah, I think, I mean in terms of outsourcing overall. I’m a huge fan of doing it, especially for things like food and beverage because like opening an attraction is hard enough. Opening an attraction and a shop in a cafe, in a parking lot and everything else is like opening four or five businesses at once.

They’ve all got their own sort of rhythms and procedures and processes and staffing requirements, and it’s, it’s all complexity. So I think for the, to the degree that you can outsource some of that. And have some strict terms in your contract that you can review that at the end of year one or year two.

When you’re then ready to take on that complexity, it helps you reduce your sort of ready requirements and you can learn and lean on that operator and then sort of be informed by how they work rather than having to reinvent the wheel on some of those auxiliary lines. In terms of ticketing, I think that that sometimes is like dependent on what the visitors buying mechanisms are in the experience that you are, you are doing.

So for example, if I was opening a new tower top like viewing platform, a lot of those are quite highly sold by. You know, ticket resellers and, you know, the city passes and these sorts of things. So I would sort of sign up to that. A disclaimer on that being, of course you lose a little bit of commission and price point on the ticket, but of course, open up to a new market, which is really great to build in some of these layers.

It’s probably a helpful experiment to run anyhow, to see if it works for you or not, and just keep things um, again, agile around that assumption. But also like right now, I think this is gonna be a real moving area of the industry. With chat, GBT and the likes of generative ai. Maybe one day, one day soon.

That won’t be something that visitors do and they’re instead purchasing through that channel. So maybe especially make sure that you model out what that looks like for you if you lose some of your, you know, if you don’t plan on using like an OTA and then you end up selling tickets through chat GPT in six months time and and having to give them commission ’cause they’ve now got a monopoly on that visitor relationship. I think there’s quite a, a high risk for the industry overall, but especially for new builds.

Pierre: I mean, I’m with you on, you know, you made a couple of points here, but I’m, I’m 100% with you on. If there is something that you can outsource to make your life easier, do it like retail, F&B. If you find folks that it is their core business, right? You’re gonna have fine folks that are running cafes for digital attraction, and they only do that. And you’re gonna have folks that run retail and they only do that. You’re right. Get these folks in, learn from them, and then you can decide whether or not you wanna do it yourself and, and show that there is no strings attached. And then the second point is that.

It will be, I will have the same approach, sorry for any systems that are put in place. You know, in my new venue, my ticketing, my retail system, whatever I have, I’ll make sure that you know, I’m, I’m flexible on contract terms. I can get data in and out at will because if I want to change to a different system, I want to get my historical data out to either migrate or, you know. Keep that to a new system.

Angie: Amen. How many, how many attractions have we seen that have churned through their uh, source systems on point of sale in the first year? Sometimes more than once.

Pierre: exactly. And, and, and it does happen. So to be prepared for that. But what, and again, it comes back to that point. Do you know that MVP do the basics, right? You will make changes along the line. You need to be agile enough to make these changes along the line. But you need to be prepared. For these changes. And by doing all these sticks here, be like, okay, my, you know, my ticketing system, yeah, great. I can you know, have an open contract or I can change that after X and I can extract my data and this is how I’m gonna do it and my retail software, I can have an open contract and I can extract my data, et cetera, et cetera. So make sure . The systems that you put in place are flexible and agile, not just yourself. And then the you know, third point that you made around you know, third party partners about the competitiveness of, you know, the industry and how chat GPT will come into the mix. I’m thinking. From the get go. I think for me, I will go all the channel that I possibly can to create awareness at least. And then again, you can almost, you can refine that, right? So you can say, well, these guys are charging us too much commission. We’re gonna stop with these guys, but we’re gonna keep going with this box. And et cetera, et cetera. So, you know, you can make these changes, but create awareness first. It doesn’t really matter how much commission you’re paying at first, you can always review that. You can renegotiate, you can stop your contract and join someone else,

Angie: Yeah, that’s, I mean, you said channels are layers and, and nothing’s hosted to the truth there. That, you know, sort of building up, whether it’s the things that you start with or the things that you end up with. You essentially like layer channel upon channel upon channel.

Market upon market upon market. And that’s how you end up with your, your growth position is, is all of those things. There’s no real sort of silver bullets out there that are going to bring in. Everything from this one place. It’s about working out in your marketing strategy, how you can layer on education, relationships, and group tours and tourism and cruise ships, and all of these sorts of things to build up that, that demand while keeping yourself excellent at those basics, like offering a great visitor experience.

Offering superb visitor services, which is where I wouldn’t go ever go as far as outsourcing the actual ticketing operation at its core, like as some crowds do. And there’s some food and beverage and retail operating companies who go after that sort of business process. Outsource of trying to get hold of that admission as well.

And I think like that for me is a real core. You know, core capability that, that needs to be in-house for an attraction. And then of course, that relationship with the visitor to the extent that you can have one before, during, and after their visit. For them as a, as a customer or a guest or however you consider them.

That’s like your core value as a, as an organization as part of that. And again, you know, try not to give that away where you, where you can hang onto it. And that’s, that’s sort of the threat of gen ai right? Of. Essentially they’re taking over that relationship. Some of these sort of city portals are, are doing the same.

And you lose some of your, your value and your growth opportunity when you don’t have that direct. So to the extent that you can hang on to those things, I would. Speaking of visitors, Pierre, I think one of the big questions that comes up in the planning process is trying to work out how many visitors to expect.

This is a very controversial topic because what typically happens from what we’ve seen is however many years out from the bill that the fundraise happens, whether that’s private capital or banking friends, family and fools as they call it, or fundraise. Corporate investments. However that happens.

There is this study done at some point that, and that number is then used for that fundraise. So typically they’ll get in like some consultants to do this. I always think of real estate agents who specialize in attraction real estate are the best at this because for the most part, the location you choose.

State, city specifics in terms of within the neighborhood and street and the footfall of the, the area this is really hugely going to govern your visitation performance. So I always think that there are good opinion to, to refer to, but early on, often before that real estate is even chosen.

Despite the fact that it’s a, a necessity to know what that number is, this big number is chosen and it’s held up through the fundraising, and often the team won’t come back and revisit it if at all until quite close to the day. And as we’ve seen from some of the new builds that have opened over the last 10 years, that number is usually drastically wrong.

And it’s usually drastically overstated. So sort of working out how many visitors to expect is a, a really big thing of of that. It’s easier if you are in an organization where you’ve got other venues elsewhere, where you can sort of look at what’s typical for one of your locations, how your new location compares on some of that metadata.

Sort of look at your. Visitor origin market and sort of work out what your catchment is and how that compares to population and tourism numbers. But this is, this is a hard guess to, to take and it is a guess until we open and find out what that number is.

Pierre: Yeah, 100%. I mean, I’m with you on, you know, the real estate piece and, and you know, the folks that are close to to the real estate will know a little bit more on the expectations, but. But it is a massive guess. And, and you have to take so many variables in, in consideration. And also, right, we, we spoke about different attractions that may be around you you know, what numbers are they pulling, et cetera.

But you may have, you may be somewhere that nothing is comparable to yourself. Right? And, and the only other attractions are such that you can compare yourself to is anything that’s related to entertainment, right? Such as like cinemas. Malls you know, restaurants, et cetera, So it’s, it’s a very, very tough one to find out.

But, but my take is that right, is that when you open a new venue, when you are busy to attraction we are in the entertainment industry or maybe the cultural entertainment industry for you know, some specific places. But this is what you are you know. If we grossly put it competing against you, competing against any form of entertainment, any form of what we call in fresh passed on.

Right. Which is like how you spend your time, essentially during the time business. So how people are gonna spend their time. You’re competing against these other folks,

Angie: We need this word in English. What was it?

Pierre: which is, I, I don’t even, it is applicable here. You know, it’s. Passed on. Yeah. It’s, it’s how you, how do you spend your time, right? So how do you spend your free time, essentially? And there’s many, many, many ways you can spend free time. You could be staying at home watching Netflix, or you could be going to a museum. You know, it’s, there’s, there’s a few a few hundreds way to spend your free time.

Pierre: Yeah, I think one of the things I like to encourage new builds to do is to revisit that number at least once a year. You would be, I know that sounds ridiculous, but like there are some attractions out there that take five, 10 years to come to fruition. And they don’t revisit that visitation expectation figure until, you know, they reopen.

And it’s 10 years old and maybe the pandemic’s happened in the meanwhile and the market’s shifted quite significantly. So, I would suggest at least revisit it once a year during your lead up to opening, ideally more than that. Because you start to, you start to learn things as you go.

Maybe like you mentioned, a new movie theater is opened. Maybe the neighborhood is gentrified. Maybe the population’s grown, maybe the tourism market’s shrunk. Maybe you’re now in recession times where you weren’t before you were in an economic boom time. Maybe you’ve now got your. Building plans, and you can start to think about your square foot capacity and what that means for either fire safety or visitor happiness.

Maybe you’ve got your sort of, time ticket and receipt of visitor processes thought out, and you can start to think about what your numbers mean in terms of actual throughput. Of how are you gonna manage that capacity? Maybe you’ve got your designs for your experience and you can think about pinch points, like have you got an escalator or an elevator or something like that that’s going to, to hold up your capacity somewhere in your experience and become a real disruptor, which we’ve definitely seen a few times.

So keep revisiting that number all the time until the point where. We’re sort of in that last year towards reopening, particularly the last six months. And at that point we’ll take that number and start to compare it to. Neighbors, peers similar like venues and, and that’s where Dexabit can come in with our unified forecasting model and data from sector to start to provide you with some preliminary forecasts for opening using ai.

Where we can predict that visitation down to the day. And at that point we can start to use that for more granular financial planning and also all your operational planning and eventually scheduling to work out how many staff do we need at what time of year and what does that look like for our workforce on the front line and how does that translate into all of these assumptions that are going into our business model as well. So that’s something that we can do at that stage, but in the, in the lead up to that, definitely keep revisiting that all the time.

Angie: And we really open about that number, right? We, we need X amount of people. Yes. And, , how long do we give ourself until we reach that goal as well, right? Like, we want a million visitors. Yes. What in the first year? Or do we want a million visitor per year in the third year or in the fourth year? Like, let you know, be realistic and, give yourself enough time to reach. Target. Right. Otherwise it may feel a little bit depressing to, to have these high expectations from the get go. And we, we can’t really see Angie, but she’s smiling right now which she fully understand what I’m saying.

But, you know, as a as a side note you know, my, one of my mom’s friend went to the doctor, slightly overweight, and the doctor told her, you need to lose 10 kilos. She was depressed, and when she told me that, I was like, man, that doctor needs to get another job. Because he fully did not commit to a specific timeframe for her, right?

He did not come up with a plan. He just gave her a number and he gave her no context. Instead be like, well, if you can lose one in the first two weeks, that’s great. And then one in the third week that’s even better. And then you’re on track and, and you can lose your 10 kilos over six months. Right? But coming up with a number and no timeframe. Can be either a really big shock for a lot of people, but it can also also feel a little bit depressing for either folks in the frontline or folks tracking this number on, you know, daily, weekly, monthly basis and, and see that number getting further and further and further away from when they need to be throughout the year.

Pierre: Yeah. And speaking of of throughout the year I think as well making sure, not only are you simulating what those scenarios look like for good. Great and oh dear, in terms of the first year of opening, but also thinking about what do they look like across year two and year three? Because typically what happens is you have a huge amount of hype around your opening.

You’ve seen this before, right? Pierre Lake and numbers are great. They start to wane. You get this big boost when you come into Year Two’s anniversary. If you play your cards right, that starts to wane. And by year three you get a big drop off. And what’s happened at that point is that everybody who lives locally has visited once if they were going to, and at that point you’re shifting to a different pattern where you are looking for net new visitors, like people who have just had kids or something that have now in your target market and your tourism market, if you’ve got some catchment from that, and people who are now.

Into that mode of being a repeat visitor, if they’re going to be. And so it’s quite a distinct demand pattern and often it’s. Oh dear. We have to manage this capacity issue to, oh dear, we have to manage this growth and demand issue, which is a totally different mode of thinking. And at the same time, you go through normally this big churn of your staff at about that point as well.

So you, you have to cope with like all of the disruption and knowledge loss that happens around that because these people came to build something. They’ve done that big job. They’ve had that amazing career experience, that lifetime experience, and they go on to the next thing and take that with them. And that’s just a natural part.

And it’s, you know, there’s a lot of burnout and, and everything else involved in those builder teams too. And they’re two quite different skill sets and interests in life of people who build things and people who run things. So coping with that sort of year two, year three transition is really tough.

If you haven’t. Talked about it and planned for it and assumed it was gonna happen and, and just sort of thought, oh yeah, one’s gonna be how it’s always gonna be.

Pierre: Absolutely. Building and sustaining are two different two different things. Right. And they are, they usually involve different teams, different skill sets. And you mentioned something very important here, is that how to retain that knowledge from team A. So it can be fed into Team B you know, after a year or two years, right?

Like we spoke about systems a little bit earlier in that podcast. You know, it’s, it’s important to keep that knowledge somewhere as well because as you say, people move on. You don’t want. Their knowledge or you know, their knowledge should be trapped somewhere that you can access or that knowledge go with them. So you need to have system in place to capture that knowledge, store that knowledge for the next person so they can either ramp up quicker or identify what’s not working well or what’s not being, what’s being put in place that is not working well so they can change it.

Angie: Yeah, and that can be everything from, like, for example, on the data side making sure that your recognition rules and all your reporting and things is automated, that all of that data transformation is automated. Because if you’ve got, you know, the analyst who’s producing this stuff. Either manually or through their own pipelines, and then they leave and that knowledge goes with them.

You know, they’ve just walked out the door with your core reporting. Or it could be, you know, your visitor services manager, making sure that they record. All of those experiments in the Almanac, because what happens if they go and then you can’t forecast anymore because they’re the ones who knows in their head that a rainy day does this.

Or they’re the ones that have gone through and done that experiment to say, well, what happens if we open on Saturdays at this time? Rather than that, and, you know, you hire somebody new and they’ve got a, you know. We learn that often by doing from scratch. So, being able to make sure that all of these sorts of things are captured, that they’re systematic rather than, like, knowledge held in people’s heads is super, super important for new build teams because of this churn employee churn problem, which is, is just inevitable as, as much as we would like it not to be.

Pierre: Yeah, What I wanted to also mention is, you know, we spoke about USP core offense, a unique selling proposition that, that, that your venue come with. That can also change over time, right? As you tailor your offering, as you tailor your experience, you may, you may offer something different, you may offer something new play on that card.

Right? We are we’re lucky enough right now to have access to feedback from your visitors. Right there, right now. Like you go on TikTok, you go on Facebook, you go on Google, you have access to all that feedback people give you, take that feedback, tell us us feedback based on that feedback, right? Again, that agile point, but it’s really important not to sell anything in stone.

You can have a new venue opening around the corner. You can have a change in the public transport that will affect your venue. So how are. You know, based on, on, on this information and what are you gonna do about it to, to make sure you stay relevant.

Angie: Yeah. So, thinking about that data piece um, sort of the lead up to operation, I mean, for if you’re out there and you’re building a new visit. Attraction we’d love to talk to you and you’re welcome to talk to us as soon or as late as you like. We’ve talked to teams who are building your attractions where it’s just an idea and, you know, we always love hearing about what’s coming up and although we probably won’t be a piece to play until a bit later down the pathway, once the funding’s done and the site’s chosen and the designs are drawn up you’re more than welcome to reach out to us to see how we can help between now and then.

Likewise at the other end of the scale. You know, we’ve had visitor attractions rock up and, and we’ve said, when do you open? And the answer has been an X number of days. And we’ve got there. It’s been a push, but we’ve got there. And then also of course, the ones that have actually already opened and they, and that sort of very chaotic year one and worked out that, oh dear, these this sort of way of operating isn’t gonna serve us.

And, and we can’t do this, that, and the next thing. And we’re wasting all this time doing this reporting. And the data’s not getting up fast enough to make moves. We don’t know what’s going on. We haven’t worked out where our markets are. We’ve either got a capacity issue or a demand problem. So, definitely we can respond to the urgency of that need as well.

But in an ideal world, it’s best to start talking twice, roundabout, sort of a year out from opening and try and sort of make a commitment by about nine months out from opening if you can. And that gives us a nice runway towards opening. We like to, we usually say give us 90 days to, to go through sort of onboarding motions in a new build.

It’s better to have double the time if you can, because often the questions we’re asking are not things that you can answer straight away because you’ve got to invent the wheel. So we say, how do you wanna recognize the revenue on your tickets? And that prompts a discussion with your team rather than just a quick.

Bang answer. Here we go. And also you’ve got a lot of our other stuff going on apart from data. And we ideally like to be out of there by three months in the lead up to opening because if you’re still you know, designing reports and things two weeks out from when you’re opening you know, your team will probably want to be doing some other more important things getting the actual physical space and, and the teams prepped, ready for doors open.

That would be my suggestion is sort of start thinking about that a year out. And also we can start to make some very important suggestions in terms of other systems that you’re selecting or being or implementing. Like making sure they’ve got decent APIs so you don’t end up being one of those ones that has to swap out the POS system in year one.

And then again in year two. Or making sure that you’ve got your electrical wiring in for your footfall cameras and you’ve thought about with us where those are gonna go rather than being an afterthought ’cause they’re more expensive to put in aftermarket after your build’s complete. So, all of these sorts of things we can address with the right timeframes.

Of course, we’ll, we’ll work with what we’ve got as fast or as slow as that, that might happen. But yeah, that, that would be our ideal. What have you seen sort of Pierre, as that sort of sweet spot in your timeframes?

Pierre: That’s a great question. I’m not sure. I mean, yes, it is nice to have time. It is nice to have time because with time you can then give extra recommendations, maybe point out to a specific route if you think the route that was chosen is not the right one. So I’ll say definitely in month rather than weeks and days is ideal because you have time to adjust. So that. You know, you, I think you mentioned that like 90 days that’s like sort of perfect timing, right? You can still have run a few herons, you have a little bit of time in front of you to adjust if you need to adjust, et cetera, et cetera. So I, I agree with you on that.

Angie: Have you ever seen the new build open on time?

Pierre: Have I, I don’t, I don’t know. Not that I can recall. Not that I can recall. Not the ones that I, I can recall. No, but it is part of the game. Right. And I think it’s tied to what we were saying earlier is that there’s so much that outside of your control, and it is, it is what it is.

Angie: Yeah. And probably another reason for the ‘m’ in MVP like keep things minimal and it’ll help you get to that that opening date and that opening budget easier and just to look to add those things on later if you can.

Pierre: 100%.

Angie: Well, one last note to those of you out there that are building these brand new attractions thank you. Like, I think it is just the, the coolest thing to do for the world to. Gifted a new attraction, and there’s just so much blood, sweat, and tears as that goes into these new attractions as they come to life.

I think it’s an incredibly special thing to do as a team, to be involved in, in your career. And it’s such a cool thing to think that it will be here for generations to come in the future. I just think that’s, that’s so special. So, to everyone out there who’s busy building, thank you and thanks Pierre.

Pierre: Thank you.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Susan Nguyen and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: How’s it going Susan? Everybody loves Monday?

Susan: It’s good. It’s good.

We always have a quiet day on Monday, ’cause it’s still Sunday in the US. We get a moment to take a breath. Today we’re always, we’re having a chat about onboarding dos and don’ts and Susan’s amazing hacks for coming into Dexibit as a new customer. I think it’s one of those areas where people always have a thousand questions before they get started. Susan, it would be great. Maybe we could start off with sort of getting into, a bit of an introduction to Dexibit’s onboarding philosophy, the anatomy of our five step process. Can you take us through some, of that?

Susan: Yeah, absolutely. So we’ve got a prescriptive methodology for onboarding at Dexibit. And that involves three workshops plus a user training session. And we work in two week sprints. So we’ll have one workshop. Give you two weeks, give yourselves some time to collate what you need for the next session.

And then we’ll have another workshop followed by the third. And then finally, user training before we shift to our monthly business reviews. And so our onboarding framework is really designed to help you configure and set up your basic support structure for the systems that you want to integrate. So it’s really hyper-focused on connecting all of your core systems and getting everything ready for implementation.

Angie: Sort of years of experiments and experience boiled down into a little bit of a method here that we prescribe.

Susan: Yeah, so we definitely wanna make sure that everyone involved, it’s gonna be including your key stakeholders, so we want IT there, we want OPS there even marketing, so people who have the knowledge around your business roles for each of these systems. And then everyone else that will be using Dexibit can join us a little bit later. So we just wanna keep the audience small and focused to start with.

Angie: And you mentioned the MBR word in there. Can you talk us through what a business review is?

Susan: So a business review is just a time for us to continue to meet once a month. So onboarding very focused on getting everything set up. A business review is allocated time for us to deep dive into your data together. Often when we start our business reviews, there’ll be some carry over from the onboarding process, but we’ll still be spending time together, configuring your roles and diving into insights on any themes or topics that you’re interested in.

Angie: And it seems like sort of doing this in two weekly sprints or cycles feels like quite a long period of time between each of these working sessions, but there is always a little bit of pre-work, a little bit of homework, right? From each one of those workshops.

Susan: Yeah, so after every workshop there will always be some action items for the customer. Whether that’s getting clear on what visitation rules are for some customers that might be already known and already set. For some others, it might be something that they want to revisit and reset. So, just depending on where the customer is at in their journey, yeah, we’ll just set some actions for you to really, really define those so that we can make sure we’re configuring them accurately in the product.

Angie: And so before we do these working sessions, we have a kickoff where we talk about sort of just reviewing overviewing the data program from, for anybody who’s new to the conversation, we can at that stage demo the product if anybody hasn’t seen it already or if you’ve got new people that you’ve just started with, we can set goals and things for the onboarding itself and then talk through the method and sort of get into the details of who’s coming to what and when, and any internal milestones we’re planning around and things like that. What’s your opinion on who should be at the table in that kickoff?

Do you prefer to have a small group of just like the change champions and leaders, or do you like to have everyone and their dog at this session to participate in the conversation? Which one do you think is best?

Susan: Definitely a smaller group, so you want exec sponsorship there. Definitely. And just key players in operations and IT, the people who have access to these systems, the people who have the knowledge, that will help us pull out what we need from these systems that we’re connecting. And then also the people who are forming the strategy for your data program. Because this kickoff session is where we’ll also define your success metrics. So whoever is involved in creating those for the wider team, we definitely want them in that first session.

Angie: Yeah, I tend to agree. I think when you’re involving wider stakeholders in that first kickoff, it can otherwise be quite a long period of time for them in their minds between when they get kickoff and when they do their eventual training, especially if there’s any delays in your onboarding process or whatever. Or if you maybe choose to stagger your training so that maybe you roll out different user groups, different times. And that can feel like a drag to them if they’re waiting. So if you sort of treat their user training as a bit of a kickoff for them, it can, it has a bit more momentum. And has a bit of change impact for those individuals versus the people who you need actually engaged in that onboarding process to get questions and answers out of, to get things, everything configured out.

Susan: Yeah. And we also don’t wanna get too many cooks in the kitchen too early on. Just because as Angie mentioned, we wanna get some answers and have a clear path forward and get things done in a reasonable amount of time. And sometimes we can have a lot of voices in offering their thoughts and ideas, which is really wonderful.

These are workshops and they’re designed to, you know, have that conversation, but we also wanna make sure that it’s not too much to sort of get in the way of our onboarding process.

Angie: Yeah, that’s so true. So maybe we could go through step by step for each of these and sort of talk about what do we need, what are the likely action items gonna be?

Who’s gonna be involved? So, I can start this one off with kickoff. Because that’s sort of often the handover point that we have together. So once you’re, we’ve got all sort of terms cleared and signatured, the big things that I usually suggest to have ready at hand, and this can actually be done as you’re sort of finalizing commercials as well.

Is just start putting together a little bit of a folder of any data that you’ve got sitting around. Often people have spreadsheets on their desktops and things, and that can be helpful to get off the ground fairly quick. The one big thing that we find really useful is particularly if you’ve got some ticketing, point of sale systems that might take a little bit of work to get into or, or whatever the case might be, is really helpful, to have. Visitation if you’ve got daily visitation, maybe for the last year or the last few years at hand, or you can get a quick spreadsheet together on that if it’s possible to send that through. Especially if you’ve got the bandwidth to be able to do that quite well in advance of actually kicking off. That can be really cool to get a little proof of concept up and running ready for kickoff so that when we do that demo to stakeholders, it’s with your actual data versus with demo data. But otherwise being able to have that sort of list of internal champions that you’re going to involve so we can invite them to meetings, some scheduled time slots is great.

And we’ll handle the rest in terms of standing up your account. And provisioning everything, getting things like the weather assorted and almanac and things. But having those couple of things on hand is really useful.

And as Susan mentioned, involving some of these stakeholders of the key people who are going to lead the data strategy, the actual sort of project effort of getting things connected and being involved in the decision making of things like rules that during that onboarding process can be great for that.

For that initial kickoff, Susan, take us through that first workshop, that first working session that would happen a couple of weeks after kickoff. So that first other step of that five step method, that’s a data automation session, right?

Susan: Yeah. So in the data automation session, we will do two things. We’ll list out all of the systems. That we are going to connect with and often we will need to define what kind of integration we’re gonna set up. So that may require us to use some credentials that you have on hand or an introduction to your vendor so that we can work with them to set up that integration. So, whoever on your team has that relationship or that knowledge or access to the credentials or the vendors that we’re gonna work with. Very key to have in this, data automation workshop. We will also use that time to go over your recognition rules for visitation. We’ll record what rules that you have set, how do you define visitation?

Is it the number of redeemed tickets on any given day, or is it the number of people that are measured by your footfall cameras? So that’s where we’ll really get into the details there. If you already have that defined and written down somewhere, definitely a great thing to send through prior to the workshop, but we’ll also just use that time to have that conversation so that when we’re ready to connect, we can set all of those rules exactly as we’ve discussed to make sure that those rules are configured.

Angie: And if you don’t have it written down, don’t worry. ’cause we see that very rarely. It’s not often that we get a customer who’s got their, their recognition rules documented, let alone even a data audit of what systems they’ve got. And that’s totally cool. Like, we’ll dive in there.

It doesn’t matter if we’re finding out some of this stuff along the way It’s just how it is in reality in most places.

Susan: Yeah, and a few actions that come off of that meeting is, one with us. We will get the initial data loaded, configure those rules, and then the action for you is to check that data.

So this is what we call the data integrity checking process, which we outline for you. And it’s just a matter of you looking at the numbers that are based on your visitation rules.

And then checking them against your source system and making sure that you have a match. And this can be an iterative process. As you know, it might be something that you’re revisiting as a team, how you actually want to define visitation.

It’s not uncommon for us to see customers choose to change a few things in here and redefine that. So, yeah, it may just take a few steps, but the data integrity. Process is something that we’ll do for every system because we wanna make sure that everything is accurate, and reflecting the numbers that you expect on your end.

Angie: And then the next one after that, and we can juggle these around depending on what order they make sense for, for your own deadlines or your situation. But usually the next one we do is around forecasting and planning. And

then. or is it reporting? I should know this dashboard and report design. So, what we need is inputs for these ones. It’s useful to have a copy of any reports that you are currently using. And this could be like a spreadsheet or a PDF or even an email that’s being sent around staff. Or if you’ve got an existing dashboard solution, some screenshots, or a share of that. It doesn’t matter how ugly they are. We’ve seen it all.

So don’t be afraid to send them to us. And it doesn’t matter if you don’t like them or you like them a lot. If you like them a lot and you want us to achieve parody, just send them along and we’ll do our best to match. Or you can send us a dashboard and report and say, hey, I hate this for these reasons. And we’ll work from there on some improvements. One of the most common things we see is that most existing dashboards and reports or or emails or spreadsheets or PDFs are just tables. So the, one of the first, enhancements that we make is usually to throw a few visualizations at them, but. People are usually quite attached to tables as well. So, we can keep some of those in there as well. But it’s getting a reference of what you currently have already is a really important starting point. And some great stakeholders to involve in that discussion are the people who are major consumers of these reports.

So it might be some of your leadership who are looking at these sorts of things, or maybe some cis admins who have been producing these sorts of things. So that’s a really great one to have and a good action out of that. One is getting these reports signed off if you do feel like you need an approval process on the design. Because one of the really big key items we like to achieve is get some of those reports even as simple as like a daily visitation report scheduled and automated to go out to everyone. ’cause it’s a great quick win to really starting to help people use data through Dexabit to get that, automated so it’s landing in the inbox every day or every week or whatever the situation is as part of, sort of onboarding with data.

Yeah. What’s the next one? From there, Susan,

Susan: the final onboarding workshop is on goals and forecasting. So ideally before this workshop, you’ve shared your goals or your budgets with us. So that would be around visitation, maybe some admission revenue, retail revenue, anything you’ve got, and that could be one figure for the whole fiscal year or a monthly break down, however it is that you wanna provide that, we’ll upload those so that we can track them against your forecasts. So for this workshop, we will activate forecasting for visitation and we’ll take you through exactly how forecasts work, in Dexabit, and how to use them for strategic planning.

Angie: This is a really interesting conversation when we get to this working session because there’s actually quite a bit of a change involved in this discussion.

People who are going from doing forecasting and planning the hard way by either grinding it out and saying, you know, Easter was here this year and, but the weather was like this and we had this closure here unexpectedly for this reason, and next year we’re expecting these things. Or they’ve just been guessing at a high level or, we’re sort of just picking a number and putting that down as a target. And so that, that’s actually quite a big leap to make for culture and for process and procedure to get to the point where we’re using, forecasting. And then of course we have the complexity of technology to learn about machine learning and develop trust and confidence in that as well.

And so just expect that with this working session, that a lot of that is about that part of the conversation as much it is as it is about the practicalities of it. What are some of the action items that come out of that one? Are there many?

Susan: I think at this stage, by this final onboarding workshop we have, we will want your visitation rules to be set. So as I mentioned before, through the onboarding process, for some customers it might be something that, you know, is calls for an internal discussion. But forecasts are trained on your visitation rules. So anytime you make changes to them once they’ve been configured, the forecasts will need to retrain themselves.

And so it might be a little bit of time before they settle and reflect accurately what your forecasted visitation is because they’re based on your rules. So yeah, we definitely at that stage hope that you have those set, and that’s why visitation is a real priority during the onboarding process.

Angie: And that’s often someone like, finance or assist admin or someone like that who’s doing that data integrity, acceptance and getting that authorization to us that yes, we’ve got the right numbers, both coming outta the system and being recognized on these core metrics.

Then we get into training. What’s your preference? Do you like training everyone all at once or do you like doing it in a staggered fashion?

Susan: I usually recommend splitting this user training into two separate sessions. So one designed for admin users, these are the people who are gonna be in the product the most and who need a little bit more control.

So they’ll be able to decide what changes they wanna make to the data, what transformations, who to invite to the product. And then the second session would be a standard user training session, which you can invite, most stakeholders too. So it would be a basic overview of the product. But normally with user training, I wouldn’t recommend inviting everyone ’cause everyone’s sort of in a different mindset of what they wanna use, Dexibit for, how they wanna use it.

So sometimes it’s good to just split it into two, just to give two different overviews and we record this session so that they can be used as a resource for the team.

Angie: Oh, that’s a good idea. I think, this is often too where we’ll see some deviation between special cases like multi-location portfolios where often we might attack, say, the head office stakeholder group first, and then we might go sort of region by region or franchise by franchise depending on.

How that rollout is planned out for or in the case of a new build often at this point it might be useful just to do that. Cis admin or super user training that, Susan mentioned almost the train the trainer training. And then sort of get into the, everybody else quite close to the time because there’s otherwise can be a little bit of a stand down period between sort of being ready or being at that stage of the onboarding process and the actual build of the visitor attraction opening.

And if that, period of time is too long, then people gonna forget how to do things. So, either combining the original training with a refresher or just holding back on that second training block, until closer to the time when it can be, you know, more appropriate for them and their preparations for opening can be great.

Any sort of other differences that you notice much in multi-location or new build scenarios that can be different

Susan: For multi locations, we might wanna divvy it up by overarching department.

Angie: Mm, that’s a good idea.

Susan: Say you might want to have training for, you know, the retail crowd specifically, or visitor services specifically, or marketing specifically, so we can do that as well.

Angie: And some of the other things you might find different for multi-locations we can sort of have that same phased approach to the whole onboarding. So we don’t necessarily have to do all data all at once. We can go again region by region or we can go franchise by franchise. Sort of thinking about rolling out incrementally across the organization if you feel, that need, and then when it comes to new locations one of the things that we’ve got going on there is that a lot of the dependencies of systems being stood up, like a new ticketing system, new point of sale system, new retail partnership, whatever the case, that’s all in flux as well.

And so what we usually suggest is, first of all, give yourself way more time than you need so that there’s plenty of time for discussions to be had for the first time. Lots more decisions being made. ’cause it’s not just like, how do you recognize visitation? It’s more like how do you want to recognize visitation? And we have to discuss all these things from scratch. But when we get into these systems, it’s like often there’s not actual data in there. Or maybe we are dealing with some sample or test data that we need to flush out. And so just giving yourself more time for these sorts of things to happen and just taking your time through the onboarding process.

It’s a lot more comfortable way of doing things versus rush, rush, rush, getting ready for opening. We have done it. We don’t, don’t like doing it, but it can be done, but ideally , in a perfect world, we can, have lots more time up our sleeves for a new build opening to get all of those sorts of things started.

Any other things to add into new builds for or multi-locations for onboarding?

Susan: No, I think that covers it all. I think, a big part of it is. Just trusting the process and taking your time. But yeah, just sticking with us and aligning ’cause we’re here to guide you and help you make those decisions and help you get everything set up the way that you want to.

And I know sometimes it can feel really overwhelming when you’re just uncovering the answers to a lot of those questions for the first time.

Angie: Yeah, that can be, really intense for a new team. And definitely, you know, if you’re not sure, just let us know and that way we can sort of come up with some suggestions and answers, borrowed from elsewhere.

So I know when you do your kickoff, just changing gears here, you often at the end of it, ask the customer what their goals for onboarding are. And I love the way that you ask this question because it’s usually in quite an open-ended format and it’s always a curiosity for me of what customers say, first of all, because I’ve got to know them over the course of however long before that of all of the discussions that we’ve had that are sort of boiling down to this one point.

But also because the answers are so different that everybody gives how do you encourage a customer to define what onboarding success looks like to them

Susan: Generally I just wanna get down to what’s the first thing they expect as soon as they begin the onboarding process. ’cause what I find is that, that actually you, there’ll be multiple stakeholders on the call and you get a slightly different answer from each of them.

And. By asking that open-ended question, you have everything on the table. And then as a team you can just prioritize what is the most important objective. This is where we also discover if there are any internal deadlines that we need to align on. That’s something we definitely wanna work with you on the customer as we wanna make sure that whatever is on your plate we’re aware of and we can work dynamically to meet those needs.

Angie: Yeah, that’s where we’re, it is helpful to know we’ve got beginning of financial year here and we want this report automated. Ready for that. We’ve got this board meeting here and we want this answer to this question for that, like getting really precise and specific.

Cool. So we are gonna get into some lightning round of dos and don’ts for onboarding. Do we wanna go one after the other on some of these? I imagine Susan’s got a long list of things that she has in mind. I can start us off with one and. That is to actually make some change. If one of the things that quite often comes up for us is people notice that their recognition rules are wrong.

Might be how they count visitors, might be how they recognize revenue. And this is what this process is all about, is kind of fleshing out what these rules are and making the change if they’re incorrect. And so my first thing would be not to waiver not to, dilly dally. Is this , a word outside of New Zealand?

I don’t know how colloquial this is. But not to muck around When you do find that there are things like this that need changing, it takes a big bit of a big breath when this happens. If it does happen to you and you find out you’ve been counting visitors, either too many or too few, or whatever the case might be, the revenue’s recognized incorrectly, but be swift with your change because it can really just hugely slow down the whole process if we can’t get clearance and agreement on how many visitors you’ve got and the team then start to erode their trust in this number because they know that something’s wrong with it, but.

Nobody’s sort of talking about the elephant in the room. And it just really sets a tone for how your organizational culture is going to develop around data. And so if this happens to you and you find a problem and your recognition rules just act fast, make a decision, commit, you know, take the change on head on and move on, rather than sort of, failing to make a decision, failing to take action, and, instead of carrying that with you for months and years afterwards, I need to have it still be a problem.

Susan: Yeah, that’s a really good point. I think in the onboarding process it’s, I think sometimes there’s an expectation of, you know, answers to a lot of these questions are yes and no, and it’s black and white, and business as usual, and that’s not always the case.

There’s always some sort of transformation that comes about, whether that’s with visitation or revenue or how you want to analyze the data that you have available to you. So as you mentioned, I think it’s a really good idea to just get in there early, make a call but also you can lean on us a little bit.

You know, this is where we bring in our industry expertise. We can make recommendations. Based on what we see and other attractions around the world, we can make some suggestions and guide you through that process to make it a little bit easier for you and the team. It doesn’t all have to sort of weigh down on one person in the team or yeah, I think it’s something that we can definitely collaborate on together.

Angie: What would be one of your do’s and don’ts?

Susan: I think for onboarding, a lot of customers understandably get really excited and really eager to jump in there and connect everything all at once and, wanna get everything done, within the first few days. And I. I don’t wanna say that’s not possible, but it’s very hard to accomplish all of that seamlessly if it’s, if we’re rushing into it.

So my recommendation is just to stay on the path that we have laid out for you. Stick to the sprints, the two weeks sprints. We do give and take there based on what’s on your plate, but, I think, you know, staying focused will really, really the outcome, you’ll see a lot more success if we stick to it together. Rather than kind of going to explore other little sidetracks in this process.

Angie: Yeah, I would probably add on another one to that of a very similar line is like, don’t reinvent the process. Like really trust the process. We’ve seen what works and we’ve seen what doesn’t. And nine times out of 10 when.

Somebody wants to do something that’s very alternative to our prescriptive methods. It does go south fairly fast. And then we sort of get to the point where we haven’t achieved what we wanted to achieve and people get disappointed that we haven’t been there. And so we really wanna keep everything on track to hit these big things that we know are the big rocks between you and the data change that you want to accomplish.

And so by all means, like if you’ve got specifics that you want to do and you’ve got some ideas of how you want to customize do voice those with us. But if we guide you back towards that prescriptive method, I would definitely trust in that. It’s there for a reason and it’s there from trial and error and cuts and bruises. So we would definitely encourage you to go with it.

Susan: And in a similar vein I think a common mistake is, you know. Sometimes customers want to really, really project manage the onboarding process. And while we have this framework I don’t really recommend doing that.

Setting strict deadlines each day, each week for your team is that often results in a lot of stress and unnecessary pressure for your team. Because what happens is, customers will underestimate how much input or resource they might need, depending on the size and scale of the onboarding project is for them.

Say for example, you have multiple locations and your ideas, you wanna roll everything out to all locations by the end of it. And so you setting these timelines and KPIs and the reality is the data isn’t as, you know, it’s not as tidy and organized coming out of the vendor system as you were expecting and requires a little bit of work or visitation rules are clear here, not so clear there. So, yeah, I think just noting down your needs and requirements, but not really setting firm, KPIs and deadlines that your team will, eventually burnout trying to meet, because the expectations are, a little bit high.

Angie: Wow, that’s such a good point. I think so many organizations, so many visitor attractions, gone to data programs, wanting to be more agile and then try and bring all of these like traditional waterfall project planning processes with them and that journey to agility. It’s, . It’s very difficult when you come at that from a very traditional place of project planning and waterfall kind of rollouts.

And when you go into data, it is. Naturally, especially if you’re doing it for the first time, a very messy place. There’s a lot of unknown unknowns and you’ve gotta give yourself and your team the time to run into those and discover as you go. And it’s really hard to do that when it’s like, on this day we’re going to be doing this task and this deliverable is due on this deadline.

I would encourage people if they feel the need to do some more planning, than what we usually are on the side of is just stick to the approach and talk about who’s going to be involved and what the inputs are, and pick out a couple of milestones that you feel you need to deadline for whatever reason, and just leave it at that.

When we get into like these really big Microsoft project plans of every single activity that’s gonna have, you’re just putting a huge amount of work and administration and overhead into things that are going to be rewritten, eventually because it’s just impossible in the data space to have that much foresight to know what problems are going to involve what’s encounter with what systems or how long it’s gonna take someone to do a data integrity check. And putting that amount of pressure on your TA team just for the sake of having a plan in the first place, we’ve gotta question what the value in that is. So, I’m so glad you mentioned that. That’s a fantastic one.

Does that mean I have to go with the next one? Oh goodness. I would say, don’t just think about onboarding as the IT setup. Capturing knowledge out of the team and using that knowledge to configure, um, that knowledge into a data product so that it’s not sitting in people’s heads and on people’s desktops.

It’s about shifting culture and, getting started with data literacy. It’s about, getting some quick wins underway. It’s about changing some of your policies potentially and your processes or procedures for things like reporting or planning. It’s not about just the IT side, so don’t just treat it as an IT project.

Susan: Yeah. I think, just to add on to that, you know, if sometimes, it seems like it might just live with the technical people on your team configuring Dexibit, but often they need, you know, the team’s input to understand how are they gonna configure all the technical bits, based on that knowledge that is shared across department to department.

So again, it’s not just a collaborative effort with, the customer and us at Dexabit but your whole team, within your organization and us. One thing, that I really encourage is if you are hitting any roadblocks or things are taking longer than expected, internally, is to just communicate that to us.

We definitely don’t want to rush you through the onboarding process, so just giving us a little bit of visibility on what might be going on, what barriers you might be facing. We might help solve for those. And we can also just sort of work dynamically and reshape that onboarding timeframe or, structure based on your, your current needs.

Angie: My next one would be celebrating quick wins. I think this is great with any, organizational change that you’re going through. And there’s a great book of who, what’s it called? Something about penguins. My iceberg is melting or something like that by, what’s it? John Kotter, and he talks about quick wins being one of the, the hallmarks of great change leadership. And I think the value in this is that onboarding takes, you know, a few months. You don’t wanna wait until the very end before anybody’s got any value. Ideally, you get some of that on day one or week one or month one or whatever that looks like for you.

And so getting a quick win and being hyper-focused on that is great. Don’t let it derail your whole thing. And it all becomes about chasing this one thing. But if we can like, go, oh look, this is the impact of weather or. Oh, look, we’ve finally got, you know, a graph of our visitation compound annual, your growth rate for the last three years that we’ve never had before.

Whatever it is, just pick one thing and enjoy it. Celebrate the moment with the team. Repeat that celebration, you know, really, emphasize the win with everyone. That is the kind of momentum that, generates change and commitment and buy-in. And all of those soft aspects of, bringing a team through, through a change like this.

And I think they, they go a long way.

Susan: Yeah, I mean the way some quick wins can be achieved is by uploading your existing data. So we’ve been talking a lot about connecting data and by that I mean connecting to. Live data coming directly from your source system, whether that’s ticketing or retail. But I know sometimes it’s fun to just get working with some historical data so we can upload those spreadsheets where you may have that recorded, so that you can look at those year and year growth rate.

And you can get it all set up to look at that for the current date. But yeah, that’s something that we can do in the interim. We just don’t want it to take the core focus off of what we’re trying to achieve in the onboarding process. But, definitely a solution that we can provide during that process.

Angie: And a couple of don’ts. I would say, don’t wait until it’s time to integrate your third party partners or vendors to give the vendor the head up heads up. I think it’s a really helpful thing as you. Like on day one as you get started, just to give them the heads up, Hey, this is coming. We might not be asking for anything yet.

We might not be, getting going with any integration yet, or whatever that looks like on your plan. But just give them the heads up that it’s coming. Sometimes they have their own things that they want to plan for, and their own roadmaps or service request queues or whatever that looks like. And it just really is really helpful.

I think it’s. Gets that partnership off on the right foot if they’ve got some advanced notice on that. So just sending them a quick email, CS on the introduction, if you need to. And, and just let them know that this is what you’re doing. I think sort of expanding that communication, this is turning into more of a do than a don’t, expanding that communication, a little bit more broadly than your team when you kick off can be really good.

Do you have any, don’t Susan?

Susan: Yeah, I think maybe, don’t try to compete with the old way of doing things, so you might be transitioning away from some legacy reporting or legacy tools and, they’re comfortable and familiar. And so, you might have some stakeholders that have a tight grip on those, but, I guess, you know.

Recommend just being open and seeing what we can do and what we could possibly do better for you. So what we don’t wanna do is be running two systems in parallel, so your legacy reports, and then this new reporting tool. We wanna make sure that we’re, having a somewhat seamless transition into, the new way.

Angie: Such a good one.

And what about. Your hack, do you have any hacks for onboarding hacks?

Susan: I think the key thing to onboarding is being open. Yeah. It’s not the super rigid, strict project that we’re working on together. There’s so much that comes out of onboarding and defining these roles and looking at the data that is unexpected. ‘Cause we, we don’t know what we don’t know. And often we find some really interesting things in your data from the get go or from your processes that we’re discussing. And so if we’re open when we’re going over all of this, you know, this really a lot of room for new ideas and new ways of working that can really benefit, you.

So that’s my, I don’t know if that’s a hack.

Angie: A growth mindset. Yeah. That’s awesome. I think your, your last one as well. That’s my, usually my hack I suggest to people like upload it and, it gives you that quick win. And it helps get you to value, get you to insight faster. And sometimes, you get there and find an upload as all you need.

And then you avoid having to go through integration, which is, always a good one when, when you can. And I remember before, before we started recording, Susan and I were chatting about onboarding and our experiences over the while. And you mentioned some good ones about this good philosophy between like onboarding and implementation.

Can you talk about that?

Susan: Yeah, so onboarding is really, just the period in which, you’re being exposed to the product, getting familiar with the product. And the way that we define the completion of onboarding is when we’ve successfully achieved that. So all of the key stakeholders have been introduced to Dexabit

We are focusing on integrating your core systems and configuring. Things for your core needs. And then we’ll transition into implementation. So implementation is really a carry over from onboarding. It’s where we’re really establishing everything. And I think just the differences that, onboarding is like that first intro to Dexabit how we’re gonna get this going.

It’s an introduction to the structure of how we’re gonna get everything set up. And then implementation is when we, get everything, absolutely everything set up. And then rolling so that it’s usable, for all stakeholders.

Angie: Yeah, that’s such an amazing way of looking at it. I think, it also gives you that com comfort.

Like some people, when we transition from onboarding into the business reviews, there’s that feeling of everything has to be perfect and complete, and it might not be. And it might be that. I don’t know. You’ve changing out the system over here and went, so we haven’t integrated it yet, or we’ve still got these questions around this data integrity on this point here or so and so hasn’t given over the credentials.

We haven’t begun this thing yet. The idea is not necessarily that everything is done imperfect because, it may never be if you’re changing out systems or going through other kind of procedural or policy changes that there’ll always be some stuff that’s in flux. Onboarding is about. The special equation of things that we’ve found leads to success with data change.

Have we ticked those boxes? Have we, got our governance in place that we understand we how data should be transformed and recognized? Have we got some basic designs so that people can get into the product and look at some stuff? Be more to come. Have we got some forecasts stood up? And a plan uploaded if you use one already.

Have we talked about. What that change looks like between the two. And have we introduced our stakeholders to some training? It’s those core ingredients. Doesn’t necessarily mean that every single loose end is, chased down and, and tied off. And there will always be sort of a roadmap of carry that you have in the data space.

Data is never done. You always sort of have this ongoing, bits and pieces that you’re doing here and there as your going through changes yourselves and different systems or restructures or admission policy changes, or whatever the case might be.

Well, Susan, I think that’s a pretty good list. If you want some more details on the Dexabit onboarding, method, you can head over to our website where Susan’s written some great materials to prompt everybody and, on what to expect from the onboarding process to dive in. And thanks for sharing your knowledge with us today, Susan.

Susan: Thanks, Angie.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Where do you find a million visitors? I don’t how many, times talked a visitor attraction lately. Where two things are happening that kind of conflict with each other. One is that year on year visitation has been declining and the attraction a negative growth. And the second is that executive have issued a goal for. Extreme growth in the quite short term, and often that is this magic number of hitting a million visitors if they haven’t already. So today we’re gonna talk about how realistic this is. How you achieve it? What do you do if this is the goal that you’ve been with, and where do you find those million visitors?

I’m here with Pierre.

Pierre: Hi Angie, amazing.

Angie: let’s dig into it. So, the first thing that I wanted to talk about is actually the realism of some of these goals. How do you think about sort of looking, when you hear about big, hairy, audacious goal that’s maybe a bit too big, hairy and audacious how do you go about managing for that?

Pierre: I think I think we need to first look at when is this goal being put in place? And why is it in place? Right. You just mentioned that you are hearing very common themes when you speak to people right now is one, visitation has been declining somewhere and two, Almost simultaneously with that is that someone put a goal in place, and that’s sort of like human nature, right? When things don’t go according to plan, when things don’t go you know the way you want, you’re gonna start to wanna put a plan in

Angie: Let’s aim for the moon.

Pierre: Exactly. And you’re gonna aim for the moon, right? So, which is normal behavior. But. When we here, we want to add, you know, a million visitors or we want to get to a million visitor. The first question that we have is by when? When are you actually tracking that goal for? Is it in a year, 2, 3, 5? Like, you know, and then we can sort of reverse engineer how, what did you call it? Hairy and big is that goal, right? Like how realistic is it based on the time that you give yourself to reach that goal?

Angie: And by the sounds of it. Why as well? Because, for me, that question always, always sort of brings up like, is this a commercial thing or not? Because if it’s not commercial, then what is the motivation behind it? And if it is commercial, then what are the other options on the table that maybe are an easier reach?

Like if we’re talking about bringing more money in the door. That might not necessarily translate to more feet. Maybe it’s getting the visitors that we have to spend more, or maybe it’s about converting them into members and sort of concentrating on some of those things, which in perhaps a negative growth environment can be a little bit more achievable too.

Pierre: Absolutely. We spoke about that a little bit during a previous episode, right? Like, what is the easiest thing to grow? Is it visitation? Is it members, is it revenue? And both of us sort of agree that revenue is probably one of the easiest to do, right? Like it’s very in your control. It’s very, quantifiable as well.

Pierre: Like you can tweak a few things to get to where you want very easily. Visitation is in my opinion, at least, the the hardest thing to grow for different reasons. And one of the reasons, that I can think of straight away right now is that there’s two different kind of events, that are part of this goal or that are part of visitation.

One is that you can control some of it. Yes, you can put, you know, blockbusters exhibitions on, you can do more programming and et cetera. But then there is the other sort of events, right, that you cannot control is that, you cannot control another attraction opening in the same city or nearby. And then sort of, taking away from your pool of customers, right?

We are in the entertainment industry, whether or not you know, we want to admit it, and people are competing with Netflix, with restaurants, with cinemas- with theme parks, museums. Like all of this is entertainment, right? So. cannot control something else popping up and behavior change from your regular visitors.

Angie: Yeah, that’s such a good point. And I think if we sort of come back to the numbers, like let’s say I’ve got 800,000 visitors at moment I’m trying to get to that magic number of a million. You know, if what I’m trying to do is that maybe $10 a hedge trying to increase my revenue by like, what, $2 million?

Maybe it would be easier for me to try and get that, or at least some of that. If I got my caps on my 800,000 visitors up by a dollar, a dollar 50, like I’m already closing half that gap. And so that’s where I think it’s interesting to sort of dig into the whys. And then like you say, then map that over time in terms of what does this mean by when are we trying to achieve this?

And then like, how does that translate into that year on year growth rate? Because if we’re suddenly expecting to achieve 20% growth in a year, in a downturn market, like we’re just setting ourselves up to fail.

Pierre: What do people usually tell us when they say that? I usually hear a sentence such as, we want more people to come when it’s quiet, and we almost want a little bit less people to come when it’s busy because they are, you know, most people think of the overall experience of the visitor, right? Like some venues actually cannot handle more visitors on specific days of the week or hours of the day because they’re already at full capacity. So it’s always a. You know, I’m sure you’ve heard that before, right? It is like, we want more people to come when it’s quiet. And it’s not easy. Right.

Angie.: Yeah, the magical, capacity demand spread very hard to accomplish and you can throw a lot of time and energy and money at this problem and achieve very little result. ‘Cause like you always say people are gonna come when people are gonna come.

 Sometimes it doesn’t always result in more visitors or more revenue. And you have to balance that risk against the fact it adds a lot of complexity as well and its own cost in implementing it.

So just to think about, like when it works, it works, but when it doesn’t, it’s quite a big burden for you. It’s quite a lot of complexity to add into the visitor experience. And so if you’re not already sort of at operating close to your you’re a largely commercial organization, then it might be the right fit.

I think when it comes to trying spread demand, other ways to think problem aswell. If your filling with, you know, there’s other strategies like, know, send your visitors to different places and use things like entertainment to draw them into places.

So for example. If I am a location-based experience and I’ve got like a fixed tour where I send my guests going here, then here, then here. Can I develop a visitor journey that sends them almost backwards so that can sort of send half in one direction and half of them other. Same I’m a museum and people typically start here and go here.

Can I suggest to some of them at some point that they start over here and then come here? Or if I’m at a zoo, can I put on a feed the animal over here pull this particular out on display over here, and kind of spread visitor better through my site. So working out where you’re really feeling that capacity and solving for of those pinch points, you can can be easier than trying to spread.

 The demand across days times or using that same sort of technique through content to accomplish that. So maybe I have a parent and bubs, session some point where parents can bring young children and be comfortable going to scream and shout. Or can I offer a low sensory time or I offer a, slow time for some of older visitors at different times in the week where I’m sort of encouraging them to visit when they can versus when everybody else is maybe at school or at work.

Yeah I like that idea. And we’ve seen that, we’ve seen that starting to pop up quite a bit, recently as well with, you know, these, you mentioned the low sensory tours et cetera, et cetera. I like that.

Angie: It is things like, you know, turning the lights down if there’s a lot of bright lights, it’s turning the sounds and music off, if there’s a lot of, that going on. sort of reducing the sensory noise in all senses of the word down for maybe a particular two for people who, who enjoy or need, that kind of experience.

Pierre: I like how this has been sort of developing because there’s been just more awareness of the need to have such an experience, right? Like I don’t recall, you know, in my younger days, no, it’s not that long ago. But, you know, I don’t recall this sort experience being offered by, by places, right?

So I think it’s sort of like a developing thing and a developing environment, based on the observations, I like it.

Angie: Yeah, it’s definitely that accessibility, is priority a lot of visitor attractions and I think sometimes it’s seen as a nice to have where it should really be a must have.

I wanna come into another sort of alternative approach to, which is when you’re staring down this big audacious of say, a million visitors. Another way to solve that is to check your visitation rules. If it is like not a financial goal and it’s just sort of a we wanna hit this particular target for whatever reason, sometimes.

Working out that you’re under counting your visitors is a very big opportunity for whoever spots that first. And this might seem to be really obscure, uncommon thing, but you would be really surprised about how often, we come across this. Has a few, major wins himself in this realm where he’s found.

Places that been undercounting visitors. course we also find the reverse to be true sometimes. I, actually had one just earlier this week where when dug into some visitation recognition rules. This particular site visitors the area, sort of mingling around their attraction, and then would encourage them to actively check in and were using that check-in number as their visitation.

But of course, that check-in was optional. They’re unpriced, ticketed location, so it’s probably representative of a fraction of their visitation. Rather than representative of whole number. So if you do have a really big target and you haven’t recently audited the sort of data governance of how you count your visitors, this can be one place find, them.

The downside to doing this is of course managing the communications of where we found all of these visitors. And that can be a really uncomfortable truth. For example, in London, there’s been a couple of famous cases going back a few years where the footfall cameras. Broke silently.

In one case, a very large national museum. The light bulb next to the footfall camera dimmed and it cast a shadow on part of the image where footfall camera was counting from, and then under counted, by many, many visitors, over course of the year, which made this organization look like it was underperforming.

And so when they found it, magically found all of these extra visitors. But of course there was some big questions raised over how long had gone unnoticed for. The other sort of downside to this this, tactic, if you like, is that it will sink your per caps a bit which is just really a theoretical metric to a degree if you’re pulling the same revenue and under counting your visitors.

But, just something be considering when you are sort of messaging this out, that you might have achieved growth on visitor numbers, but your average revenue per visit will, decline if those visitors have magically come out of nowhere from under the rug. Pierre, you’ve had some, without naming any names, you’ve had a couple of examples of this, yourself that I can think of.

Pierre: Yeah, there’s quite a few scenarios that’ve played up. But, you know, an easy one is usually like not counting groups or like large groups through the door. For whatever reason, these groups tend to come, earlier than the official opening hours, and sometime part of this group actually get missed by what we call the hardware.

Again, it depends how you counting people, right? We’re talking about fruitful right now, which is usually a combination of hardware, firmware, software to you know, have access to that data. But you know, with my experience in the biotech industry, for example, every time you deal with hardware. There has to be recalibration process in place for you to ensure that there is accuracy, right? We talk about accuracy you know, on, on the ticket side and the rules in place, and this can change, but the hardware, as you mentioned, is sort of outside of your control, right?

There’s a lot of elements that could actually play or could have an impact, sorry, on the accuracy of that hardware such as, temperature, lighting you know, multiple, multiple, multiple element that could have an impact on that. So, recalibrating this or just making sure they are counting people correctly. We usually recommend like, what, twice a year? Let’s say once every six months at least to ensure the counting people correctly.

Angie: Do part of your daylight procedures. We always suggest, and you’ll never forget.

Pierre: That’s a very good point. There is other cases where you know, that specific hardware did not count either, short people, kids or people in wheelchairs because they were sitting with a threshold that was too high. So there is all of these rules, right? That, I mean, all of these instances that could literally throw off you’re using this, this hardware, and it’s not a vendor thing, it is just a hardware thing, right?

Angie: And if you’re, still manually counting with a click account, you’re probably under counting by about 20%. So easy growth find there as well to magically produce some visitors to hit this golden number. of course no real gains on the ground with that one.

So, maybe about , some real tactics to bring some real human beings , extra. What would be your first one up on your list, Pierre, to, to suggest to look at?

Pierre: I’ve said this before and I will say it again. I think new content for me is, number one, making sure your content is refreshed enough or your experience is refreshed enough and ensuring that you’re marketing this out to your user base, right? To your current, customer base. That would be one, the priority number one for me.

Angie: Good point. before you move on to your second one, one of the things to watch out for is number of advertising dollars that you’re spending on promoting your regular your regular experience. Versus the ratio of advertising dollars that you’re using promote seasonal content.

Always try and in of the periodic content as opposed to just the because will have more impact for bringing in those visitors

Pierre: No, I love that. I love that. That’s so true. That’s so true. And it, I think the key takeaway here that I have to stay on that point is that. It doesn’t need to be a blockbuster thing, right? It doesn’t need to be anything extravagant. But making sure that content is slightly refreshed right, is, is really important.

Angie: Yeah, we could add on to that. The dark periods, the reverse, like some places, just for anybody who doesn’t know who’s listening to this, wondering what dark period is, it is time usually in cultural institution where they are hosting exhibitions and there is a time when one exhibition is packed out and other exhibition is still being brought in and hung or whatever installed.

And if that exhibition space comprises quite a large footprint in the, say, museum or gallery or whatever it is, that is known as a dark period because either the whole place can’t open the visitors feel that they’re having a substandard experience and either the institution needs to offer a discounted ticket as a result or the visitors have a very unhappy experience and we do see this in reviews as quite a common theme that comes up of people by paying full price and getting only a subsection of that. And some places that we hear of these huge dark periods. You know, add up the number of dark days in a year. Again, and really question every single day that you’ve got dark period on because every day costing you visitors add up cost for your team so that they can see the extent of Because if it means working extended hours or overnight, if it means just pushing faster or harder or doing it smarter it so worth it. Having big dark periods is a real turnoff.

Pierre: I agree. Staying on that, on that new exhibition, you know, exhibition rolling topic, what is your point of view to, essentially spread out, right? The craze of a new exhibition opening? Right. What we usually see is that we’ll do, people will do a preview for members only of. You know, before the weekend of opening or even the week before the opening, what’s your view on that?

Do you like, to sort of spread out how busy an exhibition will be or, or are you against it?

Angie.: Yeah, I think having a really strong lead up we often see this providing some nice attendance spikes. And these can be directed, you know, press friends. And then of course members and then preview. So a, more expensive ticket for those that want to get in first. And then sort of going into opening.

One of the quick tricks on this is that sometimes you’ll see say a museum or a gallery opening an on a Sunday and doing a preview on a Sunday, and then sort starting the week. I would always advise against that. And what we see is that, when you do your previews on say, Wednesday, thursday, and open on ideally a Friday or Saturday, ideally time, the beginning of that for maybe a public holiday weekend or maybe the beginning of a school vacation or something that’s going to give you that seasonal lift at the same time you get sort of your maximum bang for your buck on on that growth of the opening.

But we do see some quite interesting behaviors. Usually in the days in the lead up to an exhibition, you’ll see a decline in visitation as people hold off their visit to come. Then you’ll see of course the big booms at the start. Usually some sort of exhibition lifecycle curve, which might sort of, bell or buck over the course of the exhibition, depending on how long it is and how strong it is. And then that FOMO tail it typically starts about 80% into the exhibition. So 20% to go, where you can really start to change your advertising message and say, get in now before this thing closes. And the more you boost that message, the higher that peak of that tail can get.

So I would go really hard on that. And then of course, slightly after the exhibition, often you’ll see that softening as well. So just expecting those attendance declines pre and post and really making the most of your peaks at the beginning and end, will help you maximize your visitation over the course of that.

But yeah, make sure you start that preview on a Thursday, open on the weekend. And don’t just start up with the first day of the week.

Pierre: So it sounds like we have a good strategy to maximize attendance during an exhibition that will get you closer to your new big call. Another one that I usually find is that some institutions have usually one day of the week that they’re closed. And very often, I’m very surprised to hear that day is a Monday. Now we know here you know, in Australia and New Zealand as well as the United States and actually pretty much. I mean, not pretty much, but in a lot of countries around the world, public holidays usually for on a Monday and public holidays are huge driver of visitations. Especially if it’s on a Friday or on Monday.

We see people taking an entire weekend off. They usually travel, they make a trip out to a destination and it’s a huge driver visitation. . So when I hear that. My initial thinking is that if you need to close one day a week pick a Tuesday, not a Monday. And you know, some people are really receptive of it.

Some people are like, oh, but we open especially on a Monday for public day. But the fact is that if people are used to your venue being closed on a Monday, it’s gonna cost you a lot. To market the fact that you open on that specific Monday for the public holiday. Right. And what do you think, Angie, I’m, I’m asking you like, do you think it has the same impact as just business as usual on Monday?

Angie.: Yeah, I mean, we’ve seen customers make this change for this reason. and also when we look at the data across other visitor attractions who are open seven days a week, Tuesday is usually their quietest day, not Monday.

So you’re shooting yourself on the foot twice by closing on Monday rather than on a Tuesday. So I’m, I definitely stand with you on this one. First of all, if you are closed on Mondays and you’re closed on public holidays, when they’re on Mondays, you’re really missing out. Secondly, like Pierre says, like if you are closed Mondays and just open public holidays, probably a lot of confusing messaging out there in the public, which diluting that.

And Then thirdly it may be that Monday would be quite a bigger busier day for you than a Now, the counter to all of this, course, is that it’s a little bit inefficient for the organization to open up on a Monday and then close on a Tuesday if you need to be closed one day a week, either for administrative reasons or just because it doesn’t suit your cost basis.

But it’s worth it if you’re trying to find these extra visitors. It’s worth it make that. That leap it can really add up over the course of the year, especially if you’re striking, you know, quite a few of these Monday-ised public holidays or public holidays that otherwise are naturally falling on a Monday.

Because when they do, they really hit big especially when they are up against that weekend. Like that gives it that extra boost.

Pierre: I like the way we’re going here, Angie, because it’s almost like we look in an entire year and looking at a calendar where your exhibitions are planned, which month, et cetera. Then we sort of like went to Granularity Finder and look at specific weeks, right? And days of the week, and now I actually wanna talk about hours,

Angie.: Oh yeah.

Pierre: how can you maximize, people coming depending on what hours you are opening. Like I remember when I first started here at the exhibit seeing some heat tables of some of our clients. And I was straightaway shocked by seeing such a small amount of visitors coming during the morning and actually these heat tables getting darker and darker in the afternoon and we’re just like. Hold up a second. You guys need to open half an hour, an hour later in the morning and push that opening time later during the evening because that’s when people are actually coming, right? And, and the others can be true. , The other way around can be true, right? You could have a lot of people coming in the morning and leaving early in the afternoon, but you really need to look at. the visitation data at this granularity to understand if you’re maximizing your opening hours.

Angie.: Yeah, it’s, I’m glad you, you added on that bit at the end. ’cause I do think that this is quite polarized and a lot of it tends to come down to the demographic and origin of your audiences. Two types of audiences that tend to come early. One is. Tourists, they sort of get up and their hotels have breakfast and they’re ready to go.

And if you’re not opening till 10:00 AM they’re walking around the city aimlessly looking for something to do and walking past your front door. And the other one is toddlers. So tourists and toddlers Pierre and I have both got them at home. They get up at five o’clock in the morning. You’re amping to get out the door, so as long as there’s something you can take them to do and, preferably if they sell really good coffee there with it you’re in. And again, waiting till 10:00 AM is really painful, especially if you’ve got a toddler that naps at midday. And you’ve gotta get them home. So at that point, you can only sort of do the one hour, one and a half hour for places opening at 10:00 AM So if they open at nine or if they open at eight, like that’s a real win.

Where places tend to do better in the evening is of course when they have a slightly older audience, in a more local audience, especially during the week. And that’s when sort of looking at maybe opening late nights, making that. Not just one late night, but two late nights. And I think that the big thing here is just look at your data, look at where the visitation is naturally headed, and just optimize towards there.

And question these assumptions because it’s like, oh, we’ve always opened from 10:00 AM till 5:00 PM and that’s like the business day for us. So that’s. That’s why we’ve sort of set those hours. But is that what your audience, when your audience want to visit? Like, is that when they actually are coming in you know, what are some of the assumptions and the reasons for having chosen those opening hours and have you questioned them?

One of the things we’ve been doing a lot of analysis of recently is comparing pre versus post COVID on opening hours for these heat tables. And often we’ll see some change or maybe looking at winter versus summer and weekend versus weekday. So really like digging in question when your visitors are actually coming and steer towards there.

Pierre: I like how you mentioned season as well, right? It is very depending. It could be very dependent on the season based on, on, on different factors, but you know, when a tourist visiting, they may, there may be a peak during the year, compared to other month of the season. So yeah, I like that. So opening hours, look at season and look at the trend, right?

Angie.: Yeah, absolutely. And speaking of, seasons, one of the really, really big successes that we see our customer base are those that run seasonal, festivity events.

So a classic, one of this is like the lights season where you’ve got sort of the lights that come on at night. Sometimes it’s marketed as a separate paid ticket, which is fantastic as well. Whole new audience, whole new opening period, or opening times.

That you can open up at nighttime for this. These events pull major, major numbers and for those that do it, they often represent double digit percentages of the annual visitation. Like it is mega, the audiences that these things pull in and often some great revenue with those, you know, you can do the, the food trucks and all of things and really them into an event. Another one that we see popular with this is the Easter event season and things like egg hunts and, and so forth. So yeah, seasonal festivity events, major pull. When you sort of zoom out and look at that year that Pierre was talking about, if you can fit a couple of these into your schedule and really develop marketing around them. The effect that they have on visitation and on the bottom line.

Pierre: So that’s, you know, to tie up the visitation, to increase that visitation. Would you agree that once you have a look at that and if you want to make some change, you also need to. Realign your resources based on the change and the outcome that you want. Right? So we talked about increasing visitation.

Yes, great. We can increase visitation during, you know, A, B, C but what we want also is to increase revenue. So you need to put a strategy in place to actually increase revenue, you know, almost exponentially from that visitation increase, right? So. For example, one of the you know, one of the scenarios that we’ve seen in the past is that a lot of people were visiting a specific venue that we work with, huge visitation numbers, right? And they had different shops, you know, within the venue and every single person was shopping upon exiting. Fairly normal behavior. But what we saw that there was a huge amount of people walking through the store, right before the museum closes. And then when we look at the store data, we actually saw that the average spend and the average basket size at the store was lower than any other time during the And our assumption was that the store staff were literally brushing people around telling them they were about to close and that they had to close the shop and the museum. And that’s sort of a missed opportunity, right? You’re making sure that your people are coming in, making sure that they’re, going through the shop, but you need to allocate a little bit more resources at the shop, for example, to maximize potential revenue from that growth of visitation no matter when it is coming.

Angie.: Yeah, that’s such a good point. Another objective is often when we’re trying to grow audiences, trying to diversify those audiences at same time. So bringing in more people, bringing in new people. And these sorts of seasonal festive events can do a really great job of tapping into that.

But if you don’t optimize for that as part of the guest experience and the staff briefing and the way that you’re allocating those resources, as Pierre says , it might not be that there is quite the push on the visitor to return. So really, really being very thoughtful and planned about that. You know, making sure that the visitor receives a special offer to, to return. That they’re sent multiple invitations and follow up about returning that the experience that they’re having is a. Great one, and that they’re not too, like capacity affected, which some of these seasonal festive events can get really, really heavily capacity affected.

All of these sorts of things can encourage that visitor to, to return and come back. A really popular one is providing them with a. Bring a friend and new come free kind of offer, to encourage them to return and then bring somebody else with them. All of these sorts of things can help, achieve that goal if diversity is part of that play.

And that works equally with other programming as well. So like, for example, if you’re running education programs, encourage the kids to go home with an offer to bring back the family and then reach those new audiences, particularly if you’re aiming for that diversification and that audience group as well.

Pierre: I love that, it is usually harder to get someone through the door once, right? And you can, you need to take every single opportunity that you have to bring them through this door once give them an amazing experience to make sure they return.

Angie.: And how do you feel about free Days? Pierre

Pierre: Ooh, you know me. I don’t like anything that’s free.

No, I’m kidding. I’ve seen some extremely good results. Coming from this from free days, right, on some of the institutions that I work with one of them who used to have three days, I think about once a month. Ad hoc introduced three days every Wednesday, for example. And. I met with them this week actually, and interestingly, they’ve starting to offer three days last year in 2024, every Wednesday. What happened is that we saw a huge increase of visitation, right last year on these Wednesdays, but across the whole year. This year, what’s even more surprising is that they’re growing against last So even they have even, though they only introduced three Wednesdays last year. Yes. 2024 against 2023 was a great year, but 2025 right now against 2024 is also great here because it’s. Almost like exponential visitation from free Wednesdays. People talk about it, they’re getting more tickets being scheduled, et cetera, and they just had more people coming through.

Even if it’s a second year and they’re doing really well, their retail is up. You know, their visitation is up obviously, but it is a very, very successful operation for them

Angie.: Yeah, I think this is a great one. If the number of visitors is just a pure play here on the goal. The only sort of place I would kind of caution against it is if revenue’s actually the goal. And we’re reframing that as a number of visitors. And the reason for that is that per caps, you would think. Kind of logic plays out that if the ticket’s free, surely the visitor will spend more at the shop and the cafe, they don’t, they actually spend less because they presumably have this view in their mind that we’re going for this free experience. And so their wallet is often very firmly in their back pocket.

And so quite frequently we’ll see per caps drop on a free day rather than rise. Even when you sort of normalize for the fact that the ticket prices, not there. So that, that’s one thing to watch out for is that if revenue is the true hidden goal behind the big visitation number it can actually not be as great as you thought it was going to be on those business lines.

And the second is that it can slightly cannibalize your membership as well. If the, the primary goal behind the membership is often a free. A free element. So, just something to consider well is just to watch out that you know, why have a membership if you can come free on a regular basis.

The reason I think one of the reasons why this particular place does so well with their free days is they are a Wednesday and not any other day of the week. So strategically choosing your day of the week you are free and that you are only reaching a select audience that might otherwise not come.

Is a really great way to make sure that you protect some of those other visitors that would otherwise come on your different days of the week. And you might even make that just for locals as well. Regardless of you’re funded, that’s a very reasonable restriction to place on this. So that somebody has to provide a proof of residence in the city and you’re not cannibalizing your tourist market who would otherwise comfortably visit on a weekday anyway too.

Pierre: That was my question. How do you feel about locals being being free and, and others paying for their tickets?

Angie.: I think it’s a really easy explanation when you are funded in that way. So like if you’re funded by a local city council or a similar state authority, it is a little bit harder when that funding explanation isn’t there. And I also think it’s the only thing that you have to watch out for is how you enforce this.

First of all, most people don’t necessarily carry a proof of address with them when they’re out and about just visiting a local attraction. They might have. Form of ID on them, but it might not have a proof address on it. So that can be a really tricky logistical thing to get around.

And you can also get yourself fairly hot water fairly quickly if your staff start enforcing that via sizing up visitors and making assumptions about where they’re from. So something to train very specifically for, if this is strategy that you’re going for, that you don’t have staff, assuming that they know that a visitor is not a local based on say, their accent or their ethnicity.

But I think, you know, if done well, why not? Like, if it’s a great way to be able to encourage your regular visitors to visit more often, even if they’re not members, and a great way to still maximize your opportunity from that tourist market. And most tourists naturally have a higher appetite for spending than a local visitor. So, um, definitely worthwhile capturing upon that.

Pierre: My last question for you around three days would be, if you were responsible for making the decision to, whether or not do a free day, would you, how would you be influenced by your environment in terms of other venues that are around you and whether or not they are either one, offering a free day or three all the time or not offering a free day and, you know, being a paid venue, would that influence your decision at all?

Angie.: Of how competitive I am towards them. I gonna pick their, , big launch day and, and choose that one. Do you mean

Pierre: Absolutely. Maybe.

Angie.: I don’t know how evil I am in practice? Depends if I’m commercial or cultural, I guess Pierre.

Pierre: Like if you were a paid venue surrounded by paid venue that never offer a free day, it’s not a bad strategy will you consider it? say Yes, I will. I will. do a free day and I will make it on a Saturday.

Angie.: I happened to have chosen this exact day. Speaking of sort of competing with the locals a multi attraction passes great schemes to, to be to sign up for. So this is, maybe you’ve heard of something like a city pass. There’s a couple of other brands out there that do them yeah, whether it’s something that you team up with your frenemies on to organize yourselves or whether you’ve got an operator in your city that’s selling these, they’re a great way to just increase that, reach a little bit more. Of course you don’t get quite the same admission per caps through them, but certainly worth a try. Only caution around here would be watch that. You are not actually cannibalizing of your locals with these. Usually you’re aiming at a tourist audience with these like people who are in a particular city for a certain period of and they buy one of these multi passes to see it all.

But often we’ll find when you dig into the origins this data, that sometimes will be using them during the school holiday school breaks. So I just watch that they’re not cannibalizing what could be maybe a membership offering something else. As well. So just something to keep an eye around.

Pierre: Keep an eye on the data. Right. We’ve seen that. Also we’ve had some surprises around that where we thought this sort of tickets were targeted for tourist and funny enough, we had a lot of locals, buying these tickets. But there’s a lot of various reasons why that maybe.

And maybe locals with family visiting from different cities, from different country and actually. Buying these tickets to take their families around, et cetera. We know it’s really common on our side of the world here, right? Like, because we’re so far away. And when you have families visiting, usually take them around and you’re gonna take that multi attraction pass you’re gonna make, you know, a few days out of it or a week out of it

Angie.: Yeah. And speaking of, the member offering. This is a really great lever to pull. Like if I’m coming back to this example where I’m 800,000 and I’ve got maybe 80,000 members on my books at the moment or something. Getting those 80,000 members to come back for one more visit each year again, can just close like 10% of, of my, visitation again. So just deliver me that extra growth. So that might be half my growth goal, for example. So this is a really good lever to pull. We always talk about it’s easier to get somebody who’s already in the door to spend more. It’s also easier to get somebody who already knows who to come back one more time.

So thinking about what can draw that member back in. Is it a special offer? Is it a special experience? What’s the incentive for that? What extra marketing we are putting down around that you know, getting that metric up. That number of average visits per member up by one point, major, major achievement on, on that visitation goal.

Often members are good spenders on the per caps as well, because they’re not paying for the admission. But again, this is depending on what the. True motivation behind the million visitors really is because if it is about that admission, margin, then this one’s not gonna work much.

Pierre: What else do you get in the bag angie?

Angie.: Oh, I know we’ve been on a rant about this for a while. I’ve got, there’s stuff around corporate team buildings, you know, B2B sales around that education and really Mark going out to market hard on that. Really treating that like a sales channel. Speaking of channels, you know, going down the channel partner route, really optimizing for that.

Talking to your, OTA partners for online travel and things like that, local guide companies especially, where they sort of turn, turn up by the busload. I think the only one that, we haven’t covered that I think we can’t not mention. Is your marketing spend and optimization. This is probably one of the biggest factors within your control, but also one of the things to think the most about because the harder you are pushing on this growth goal, the more expensive your. Visitor acquisition cost, you know, your per unit cost of bringing in each additional member, visitor becomes and at some point it’s not worth it. So really keeping an eye on those numbers and working out what that dollar value is and how that dollar value is changing as you’re reaching further and further into a stretch can really help with that.

And then getting really, really harsh about optimizing for, you know, if you’re, putting the, the flags on the lamppost and the ads on the back of buses and not really thinking about the attribution of those in terms of rail feet through the door. Some of those dollars can be, better used elsewhere and particularly online when they can, where they can be tracked.

And so really optimizing for that marketing spend. And sometimes it’s even going right, right, right, right, right down into the details. Like getting into your Google Analytics data and going, Hey, we’ve got a whole pile of ad spend going to these zip codes or these states, and we don’t actually have the visitors coming from them, so let’s chop those and focus on these markets and these missed markets that we’re gonna try out or.

You know, hey, we’re advertising this event this far in advance and that doesn’t actually match up with the booking lead time of our tickets for that, so let’s peel that back or push it forward, or whatever it is. So really like using the behaviors of what your visitors are actually doing and sort of testing and then validating that against how you’re spending, can really help you, you optimize that marketing spend.

But yeah dig deep into that space as well. So I think that’s probably all we’ve got time for and we’ve, we are maybe out of, out of juice on all of these different ideas, but hopefully that’s given you a whole pile of food for thought over where you are going to find a million visitors. And let us know what your strategies and tactics are.

Love to hear what everybody else is doing, and we constantly see such innovative things like places sending down. Recruiters down to meet cruise ships to bring people up, or, putting objects into airports to be part of the visitor greeting experience. So whatever those creative ideas are that you are trialing out, we’d love to hear about them as with the community.

So do do put them out in the world and let’s share a like, see you next time.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Okay, we’re gonna talk about failure and mistakes and tell you all of the things that we’ve learned over the years of either doing data transformations ourselves and what sort of missteps we’ve made, or often when we talk to visitor attractions who turn up to the exhibit, having tried to build something themselves and some of the lessons that they’ve learned that they share with us as well. And here with me today is Pierre. Pierre, what do you reckon is on my list? Top, top mistakes.

Pierre: First of all, I like what you say about mistakes we have made. And as, as like the point of learning. When you do some data is that you will continue to make mistakes but because you’ve made some in the past, it’s how quickly you, you react to them and how quickly you apply a fix, right? So I feel like making mistakes is a natural step in the process. It’s never gonna go away. But it’s about how quickly you react to them and what fix you put in place. So there is there is a massive learning here. But in term of what the most common mistakes are, the common mistakes that we are, we’re making I feel like a lot of time, people undervalue, the amount of work that may be implied in a specific integration sometimes, or they think that, you know, they a very good example of that would be someone going with a new vendor thinking that it would be very easy to extract data and think, oh yes, they have an API. Oh yes, they have all these fancy things. And when we turn up and we want to integrate and we realize that it’s not as straightforward as it can be. So ensuring that there is good data availability and assortment from the sources is one of them.

Angie: It’s so true. And it’s funny I was reading a stat the other day that 85% of data projects fail and the number one. So this is a Gartner, Gartner finding. The number one thing that they cite is integration difficulties and then followed by things like management resistance and internal politics, but integration difficulties upfront there. And I think in our industry and visitor attractions in particular, that’s a really difficult one because a lot of the systems are quite old. You know, a lot of the ticketing companies been around for a long time. They’re pre-cloud. Maybe they’ve made attempts to get on the cloud. Maybe the box says that there’s an API, but under the hood, not really. Or maybe there is one, but it’s, very suboptimal. Doesn’t include the right attribute, segregates data in the wrong way. All of these sorts of things. So, sometimes you don’t know these things until you get into it. Sometimes, you know, the vendor coming and can give, the customer the heads up on, on what the realities are going to be like.
But yeah, for sure. This is one of the things that internal teams, when they’re trying to build something themselves, really, underestimate the level of difficulty, not only to build, but also to maintain longer term and to think about what that’s like over generations of data teams, over generations of vendors over all of the different maintenance things.
Like what if the vendor goes down, what if they uh, retire part of their API and issue an end of life notice on it. What if. they change up how they address some attributes that there’s a lot of maintenance involved after the fact. Did I have that one on my list? I’m trying to think. I’ve got an integration one on here. One of mine would be trying to integrate all the things without actually making any forward progress on insights and like operationalizing data. So it’ll get to the point where it’s like, oh, we’ve got this e-commerce system. How much of your revenue does it comprise? Like less than 1%. Or this extra ticketing system, what do use it for?
Oh, this one event that we run each year and it’s like, we wanna integrate this and this and this and this and this, and this. And just adding a huge pile of complexity rather than getting going with the basics and just getting some dashboards out the door, getting some users trained up, getting some reports automated, like just making forward progress. I think my big lesson learned is like focus on the big rocks and get momentum going, and then for the rest, like upload some extracts if you really need the data, but focus on getting data out to the people. And then come back for all of those extras later on over time.

Pierre: This is such a good point and, and so timely because you and I had a conversation with a stakeholder. This week, right. Regarding that topic on you know, that stakeholder had limited resources, , in their team, in their budget to, to build from scratch and when they talk to folks in the organizations, everyone wants everything. But they don’t really know how they want it. And that puts a lot of pressure on the technical team, they try to build what they are being told to build without necessarily understanding what’s the end user. What outcome the team is after. And that’s certainly, you know, a mistake that we’ve done in the past as well ourselves with people telling us, hey, we want this, and hey, we want this.
And we’re like, oh yeah, we really wanna make them happy and, we are gonna get this, connected without taking a step back and be like, hold up a second. What is it that we trying to achieve by bringing this data set and how often are we gonna be looking at this data set to make it relevant, right?

And sometimes, as you mentioned, we think of taking a very complex, real time route to give, to bring data in front of them. And there may be another alternative that’s a little bit more simple that will give them the same results. But that will make it a lot lighter on their team and on our team as well.

So I agree with you. Wanting everything at once is sort of like, a utopia almost of, you know, we can have everything ready really quickly, and it’s not, it’s not always the case.

Angie: Yeah. And it’s just over investment really, isn’t it? And reality is, it just pushes out the timeframes of getting all the data integrity accepted and everything else, and getting all the dashboards designed. But. For very little gain. Like you say, there’s that often that one data set that somebody looks at once a year and it’s a bit deflating to go through getting the data all perfected.

And, only to find that nobody, nobody looks at it. Speaking of this one, I think next on my list, this is gonna be popular with you, pursuing a hundred percent data integrity when there’s little business value in doing so. People can’t see Pierre’s face right now, but he’s got that ‘oh, yes’ look.
So often we find like, oh, there’s this refund of five tickets from a few months ago and now the data’s outta sync and it missed the reconciliation window. Or, of whatever the case might be. I mean, data integrity is really important. People need to have confidence in their data. But often and often oftentimes we integrate in voila, a hundred percent accuracy, everybody’s happy. But if that’s not the case, like 99% is good enough you can spend endless hours and wasted chasing a few tickets down here, or a wholesale retail transaction down here, or trying to work out this random thing that happened once in, 2023, or every now and then. And the reality is to like to make good decisions and plans, it doesn’t need to be perfect and perfect really is the enemy of progress in this case.

Pierre: I mean, by default, I am from the school that done is better than perfect from the get go, right? And perfect has a very subjective definition for every single team in the organizations. Your finance folks will always be, a lot more focused on the accuracy that, you know, you visit to experience your operations, et cetera.
So it really depends on who you speak to. In terms of expectation of accuracy, while I’m usually here, you know, what we usually do is that we focus on insights, and trends. So the fact that your visitation, maybe up 25.01% against 25.02% is irrelevant in term of the accuracy.
The relevancy: is it up or down? And by how much. And when you look at your other data in line with that, in parallel with that, can you see trends and insights based on that? What is more important is in my eyes. More than a hundred percent accuracy and just making sure that the rules that you have around each specific data point are loud and clear to everyone.
When do we recognize someone as a visitor? When do we recognize someone as an exhibition attendee? When do we recognize revenue for. A specific ticket, et cetera, et cetera. These are really important roles to put in place. But having a discrepancy of, you know, 1, 2% in an overall report or a novel count, probably gonna have very limited impact in the medium to short to long run.
Angie: Yeah. And a big hack that you’ll find I’m giving away the house secrets here, so if we ever do this to you, you know, you know what we’re doing now. But, if you ever find yourself in this situation, like one of the things we do is somebody will say, oh this data set is out by 42 tickets, for example. We’ll immediately convert that into a percentage because that sort of puts things into perspective for people making a decision on what are the decreasing returns of chasing those last few often points of a percentage on data accuracy. And sometimes the other thing to think about as well is like the realities, of how good the data is in the first place. So a real typical one that we see with this is Google Analytics. Google Analytics comes out of Google slightly differently depending on how you dimension it and how you sort of pull that data out. But we also have to realize the fact that particularly in this changing world of cookies and now in this changing world of, generative AI appearing in search results or even just straight into conversational search or conversational content. It’s not that accurate to start off with. Sorry, Google. And so, worrying about a couple of percent on Google Analytics is, depending on how that data has been mentioned can be a bit of a lost cause as well.
I mean, the big thing is to see like, is it going up or down? How does it relate to visitation trends? What’s performing and what’s not? What’s the conversion rates and how do they change over time? That’s the stuff that really matters, rather than, was it 1,337 or 1,339?
Pierre: Absolutely. And with that there is also, when we talk about list and when we talk about impact, there’s also different updates, right? That may be made either the source or by the vendor that may affect your accuracy. You know, along the way. For example, a specific vendor pushing an update on a specific day, and you’re thinking, oh, everything’s gonna run smoothly.
We don’t touch any, of that part of the product. And then the day after comes and you’re like, whoa, hold up a second. They actually touch a lot more than, you know, specific part of the API specific part of the product. And there is now, a bigger discrepancy or there’s things that we are missing after that update.
They may have changed an attribute name, they may have added an attribute. There’s ample things that are, that can go wrong, okay? That can go different when an update is being pushed. And I think that’s one, one that will be on my list as well, is that if someone mentions that they’re making an update, you will follow up very quickly in product to understand. Has this changed my numbers, yes or no? Because things can go wrong from there very, very quickly. If you’re not aware that it has changed, the results that you’re getting from that integration.
Angie: Yeah, that’s so true. Data integrity is not a one time thing. It’s like a thing that you need to address periodically and like Pierre says especially if something’s changed, go back and check. Just do those health checks every now and then. One of my favorite areas to do this with is physical hardware, particularly like, people counting cameras. There’s been some very famous cases, like out of the UK, a couple over there where the footfall, camera counting visitor is coming through. The perimeter broke or, worse broke quietly. Where it started undercounting. I think there was one case with, um. These are very large sort of national museums and galleries.
One case where the light bulb dimmed or they replaced the light bulb with like a slightly dimmer light bulb and didn’t recalibrate the footfall counter and undercounted. We are talking about like half a million, a million visitors a year affected public funding was a really big deal in the media.
These are the sorts of things that periodic data integrity and in this case doing manual click account tests. My suggestion is always to do them with daylight savings. We are always reminded to check our smoke alarm batteries at daylight savings. Also, check your people counter accuracy at daylight savings.
So just do a manual count for, you know, half a day or something. Compare it back. You can load your manual count anDexibit alongside your people count so you can, compare the two data sets and check your accuracy, of the actual hardware as well as, the data that’s coming out of the system. Next on the list. Pierre hasn’t seen this list, so this is completely fresh. We’re getting the live reactions. I’ve got. Keeping data in the corner or the IT department. So, what I mean by this is like only the tech team are involved in onboarding and no other stakeholders are invited to business reviews.
And they put off user training and the internal message becomes something like, let us know what you want and we’ll go and build that for you. This becomes a real agility trap where we don’t achieve that. Like democratized data vision. Users don’t have the confidence to self-service their own needs. Data literacy and culture slows, and the end result is just like an IT department with a long list of requests for reports and data going out the door and that vision of data transformation really hasn’t been met. These aren’t in any order, but this would be one of the top ones on my list, I think, of impacts down the road in terms of like, have we achieved the objective?
Pierre: I like how you mentioned that and it. There’s two metaphors that come to mind when, when you mention that. First is like there is no perfect timing to present the data, right? Like, waiting for perfect timing to, to do that, for everything to be lined up and everything to be perfect is almost having a perfect timing to, to have your first child, right?
There’s not such thing, oh, I need a house, or I need more money, or I need a car, or I need this. You are always gonna need more. You’re always going to need to do something better before you do that. So do it now and then get feedback, right? Or be pragmatic about it. The other thing is it’s composing a data structure is almost like composing.
A beautiful piece of music, right? You never know how good it’s gonna be until you put it in front of people and they give you your, their feedback, right? You can write the most beautiful music in the world, but if no one listens to it, you’re never gonna know how good it truly is. And you need people’s feedback, right?
And how they feel. Same thing with data, same thing with structuring these dashboards. Pulling it to the team when it’s good enough to be put in front of the team, get people’s feedback on, yes, we like this. No, we don’t like that this, we want to see it in a different way. And then we can tailor to their needs.
Almost reverse engineering the process. Instead of saying, we are gonna do all this work here, we’re gonna put it in front of the team and happy days. It’s more about let’s put a draft together. It needs to be good enough to be, I agree, it needs to be good enough to be, uh, put in front of people, but then we need to hear the feedback, right?
You need to sell almost a data structure to the team and to sell, you need to listen, and to listen, you need to have some feedback.
Angie: Yeah, we have a release philosophy here at Dexibit but when we’re putting out product, so like developing software which is three words, and I think that makes it nice and simple and powerful and it’s, ‘little, early and often. So release something small, release it as soon as you can, and then iterate on it constantly once you get that feedback. And people talk all sorts of things about agility and there’s all sorts of frameworks in the world for. Mastering it, but little early and often. I think sort of describe the best way to really achieve that and data that can be like, you know, this is why we’d make a big push for visitation.
Like, let’s get a visitation dashboard out the door. Let’s get it automated on a daily basis. Let’s get it out to a big audience and before we go integrating all the things, doing all the fancy stuff, just even small wins like that. Make big strides when it comes to bringing everybody on the journey along with you.
Pierre: What else is on the list? Angie tell me.
Angie: Um, spending six months on a data audit and assessment without making any forward progress. This is like often something people do before getting started. And it turns into these like largely theoretical exercises. Priorities and realities always end up being different once you get into it. And basically we’re just delaying value while increasing cost. And realistically, very few people are going to really read the report that they spent the thousands of dollars on a consultant to write. And usually we find like stakeholders actually need to be sleeves up in the data to know what they want and to know what their data needs. And that sort of idea that you only know what you need to know, when you need to know it kind of thing. Like, doing a brief audit is cool. That for us is often just a conversation of what systems have we got and what are you trying to accomplish? Maybe a workshop but don’t, overanalyze don’t get sort of trapped in that analysis paralysis before getting going. Literally, like, let’s just get into some data and get started. Because it’s through these conversations and through the work that everything is revealed. And people start to work out what they, what they want and what they need.
Pierre: I feel like this is something that we’ve become really good at with the folks that we have in our team, is that we get thrown very often new systems, right, that we’ve never dealt with before. But the folks here that we work with are really good at contextualizing that data and picking up a field and say, yes, this specific field is the same as that specific field in that system.
And we should call it, for example, date schedule, right? Or date redeemed, or this specific status means, that the ticket was canceled, that it’s not valid or that it has been bought as a gift, et cetera, et cetera, et cetera. There’s a lot of this exercise, of trying to understand and contextualize the data from a source that potentially an internal team may not have been exposed before, or they may make assumption, which are not in line with best practice or with what the data was, first put in place for.
So I feel like there is that as well that can take a lot of time on going back and forth with teams. In an internal organizations where we sort of have, without being you know, pretentious about it. But we sort of have been exposed to so many different systems for such a long time that we know how things should be structured and should be looked at going forward. And that’s how we’re saving a huge amount of time right when we integrate.
Angie: Yeah, when. We’ve got a thing Dexibit, which is part of our software product. It’s called a semantic layer. And basically when we hook up to one of these vendors or source systems, we pick up every single attribute and give it a name a proper name. ’cause often it’s a field name and the source database is something really wonky. We give it a nice description to make it easy for people to work with that data to understand what they’re working with and any kind of notes that they need to know about it. We might give it some transformations that maybe it’s in the wrong time zone or maybe, the data just needs a bit of a cleanup or needs some tags or something put into it. Or maybe it needs to be enriched to really unlock some value or sort of converted and classified and things like that. And then we, give that, that system, maybe some derived metrics to calculate some stuff dynamically that it’s missing. We’ll give it some visualizations. And then we might map it into a domain and say, well, this is ticketing data and so it should look like this and get all these extra visualizations and templates and stuff. And we sort of form it. Make it conform to some industry best practices as we see them in this data model. But it’s essentially this huge pattern matching exercise. ’cause even if it’s something, completely off the wall, different. We can say, actually this is sort of transactional data and therefore it should look like this and have these things.
Or, this is location data and so it should have these things and look like this. And we’ve got the benefit of having done this over and over and over again with hundreds of vendors and lots of different data sets to be able to accomplish that. It’s very, very difficult to do. And a data audit on a piece of paper.
And I don’t want to be accused of being a hypocrite. We do have a data audit and assessment template on our website, but it’s literally there to support a very brief, um, conversation, not to spend months and months worrying about because literally once you get into these things everything will be different anyway. Speaking of money wasting, my pet peeve is data sovereignty. Which is a whole other conversation in itself, but an example of where you can spend a ton of money on something that delivers very little value and you probably don’t need. FedRAMP would be another thing, like very expensive, won’t actually change anything for anyone.
And it’s really just sort of compliance for compliance sake. In most cases, because we’re not talking about PII or PCI data here personally identifiable or credit card information we are talking about like business data, transaction data. And so sort of keeping some of these very things that can be very expensive, very time consuming unless they are an absolute necessity. And just getting really pragmatic about them would be something I’d pop on that list too.
Pierre: Absolutely keeping the right context around the data that you are gathering and analyzing is one of the key things. And, and I agree with you, it is it can be quite a massive roadblock, right? Sometimes when we have teams or, individuals , that don’t really follow that context or understand that context and what we’re trying to do. Yeah, 100%.
Angie: And then if we sort of zoom out a little bit, I’ve got here making a data, a project, not a product. Now when you implement, let’s say, a point of sale system, you get it, set it up, you get configured, you switch over, train everybody up, do your migration, and off you go. Data is totally different. And one of the things that we do at Dexibit that’s quite unique is we have a, what we call a data concierge service.
We do. Usually monthly business reviews with our customers, where our success team will sit down and run through the numbers, talk about trends and patterns and insights and benchmarks and new features and new suggestions. And somebody from, the stakeholder group that are attending those calls will say, well, I’ve got this question, or I’ve got this problem, or we are switching out this vendor, or this system, or this partner, or changing our pricing, or whatever the case might be. And we talk through the data ramifications of how to service that decision or that action. It’s a moving beast and it that you have to go with that. It’s not something that’s like one and done and you just dust your hands and walk away. So treating it like a product that evolves, that’s like living and breathing and constantly learning and improving and will always have a roadmap.
And that doesn’t mean that you’ve not finished onboarding. It means that, this is something that’s moving with your organization as it grows and changes.
Pierre: I think one of the sentence that still give me nightmares is we are integrating this new vendor and the question is, great. Do they have an API and you know what the answer may be, or we don’t know. That sort of answer gives you nightmare, right? You, you don’t know what you in for when that happens.
So, yeah. 100%. It’s almost like, um, I used to work with with a lot of, of talented folks, in the previous organ, and the model was 1% done, right? We are always 1% done. And that’s sort of the same thing with, with your data, right? It’s always 1% done. It is always evolving. It is always a moving project that you need to be agile around. And that’s really, really important.
Angie: And probably related to that is the mistake of ignoring organizational change management and this is sort of the silent killer I think, of any kind of transformation, but particularly, data, I think is, there’s a lot of fear around it. Some common spots where this arises sort of qualitative evaluation, particularly in the age of AI where people can, have some very real fears about whether AI is going to replace their job of analyzing voice of the visitor.
Or and so sort of helping them reposition as an insight leader and champion an educator within the team the wider organization’s, really important. And instead of talking about the merge of quantitative versus qualitative, not the two being enemies of each other, Gatekeeping particularly around sort of, system administrators that have been there for a long time, maybe that know all the rules and they’re the only person that people can go to, to get data from and they keep the spreadsheet with all of the things very, very occasionally, but it does come up.
There can be financial risk involved with that in terms of like, fraud and theft. So it’s a very real problem to address. And then others like are just sort of, general areas where usage can otherwise be low and people can just not engage. And just keep making decisions the hard way without data. So getting into lots and lots and lots of training. We don’t cap out our user training and that’s, that’s, one of the reasons why helping people with the storytelling aspect, helping them with the translation of like business problem through to, data analysis and just consistently reinforcing great habits, with the team. These sorts of things are really, really important for leaders. And if I go back to that Gartner thing of why did data projects fail, like, lack of leadership support or having leaders on board was one of their top ones of reasons behind the integration one. So this is definitely a big thing. The end of my list, Pierre.
Pierre: Yeah. No, that was great. And on that, you know, I absolutely resonate on that. I think, a while back now I had a conversation with the stakeholders. And we were looking at a specific part of the product, and that person said to me, oh no you know, you’re looking at this wrong.
But no you wouldn’t know that unless you were me. And that sentence is really striking, right? Is that one person in that organization, only knew a rule that really should have been known by more than one person. And it’s fairly, it’s almost dangerous, to have that knowledge isolated to one specific person.
’cause anything could happen to that person, and then you lose that knowledge, right? So, I agree, Support of leadership being transparent, documenting the changes, documenting the structure is really important to make it successful.
Angie: Is there anything missing from this list that you’d include in your top? I’m really putting Pierre on the spot here.
Pierre: When we purely speak about data and availability of the data, for me, my biggest one is how granular do we have that data available to us at? Right. It’s we’ve seen that many times where, like where the data is not granular enough. When it’s being sent to you and then you’re extremely limited on how you can use that data with other data sets that are, have a final granularity.
An example of one would be footfall, right? We’ve been in a situation before where we had. You know, tickets being bought onsite flowing hourly or an hourly granularity and your retail revenue is flowing and an hourly granularity and it’s great. And then you have food for data and that was a daily granularity and that mismatch here of granularity sort of rolled, a lot of your insights out of the window because they’re not, you cannot match them together. You’re missing a piece of the puzzle and you have all the data in it’s happy days, but because that data is not coming at the same granularity, you’re actually missing insights. So I think that’s one of the big one for me is.
You know, go as granular as you want for two reasons. One is that yes, on the inside it’s really important to be as granular as you can and have the same granularity across all the different source that you deal with. And then the second is that if something goes wrong or if you notice a problem it is, way more easy to go down to a transactional data type than aggregating at a daily level, for example. Right. We talked about accuracy very early on. If you have something that’s, you know, an accuracy that’s off for whatever reason, you want to be able to go down to a transaction or an order, for example, when it comes to retail and tickets and break that down by order or transaction.
Because if you don’t do that, really you start to guess work on what is going wrong. So that would be like a really big one for me is, you know, the accessibility availability of that data at a, we call it transactional here at Dexibit, but really as fine as you can have on the perspective.
Angie: Yeah. When P is talking about transactional data is talking about like, on Monday, the 12th of June at 12:47 PM somebody bought a coffee and it was a latte and it was large and it was $5 40 and the tax was this much, and they bought it together with a muffin. It was a blueberry flavor, and they chose to have it to go, you know, it’s this kind of level of detail versus like on Monday we made $5,347. So the granularity of that data is, yeah I would agree. Super, super important. And probably related to that, forecasting accuracy. Judging, I know that seems like a really left field leap to go from coffees to forecasting accuracy, but judging, forecasting accuracy on different granularities, you know, looking at, a target for a month and going, oh, well that’s 94% accurate. And then looking at a daily forecast and saying, oh, well that’s only 87% accurate and therefore it’s worse. Like, always keeping in mind the level of granularity that you are, thinking about when you’re talking about data or when you’re talking about predictions.
And particularly when you’re judging accuracy sort of apples for apples comparison is a bonus one.
Pierre: Yeah, absolutely.
One last one for me, which is you know, the validation, like we talk about data integrity needs to be acceptable before transformation, if that makes sense. So we do wanna make sure that we are dealing with the right data before we start transforming that data and bringing insights into play.
For example, when we talk about footfall, we wanna understand. You know, a common metric that we that we track is how many visitors came to that exhibition. Either, you know, comparing a footfall visitation against a footfall entrance to a specific gallery, or the number of tickets that were scheduled for that exhibition.
Or for example, how many people visited the museum out of. X amount of people who visited the museum, how many entered a retail store. But what you wanna understand is that you wanna validate the first two data points that you are dealing with before transforming and having the insights, so you want to make sure that one, you’re counting people correctly within opening hours and on both sides, opening hours at the museum and opening hours at the store.
Then once you have that validated, the end, you can transform into a ratio, for example, of. X amount of people have that have entered the museum, also visited the store. But don’t skip that process, right. Of validating the data before you transform or you do anything with it. So that’s one of, that’s one of my one.
Angie: Yeah, same truth for forecasting as well. To come back to that topic, not to harp on about forecasting, but I was in a customer meeting earlier this week where we pulled out the beautiful new forecast. We just, spun up and then went, oops. The visitation data is, come out incorrect on this, this, and this.
We actually need to go back and reevaluate some of our business rules. And of course, all of the forecasts were then thrown off and to constantly try and reinforce that point of, by the way, these have been trained on the data that was, apparently missing these things. Now we know and we’ll go and address that, but like, yeah, again, another example to Pierre’s point of like validating the input, that’s going into a machine learning model and training it up rather than expecting it to magically no where the input data is wrong. Very important. We could probably come up with a whole nother list just for AI as well, I imagine. Speaking of, machine learning, and probably top of my list there would be, don’t spend several years writing an AI policy before you dip your toe in the water. But there’s probably a, there’s probably another 7, 8, 9, 10, lessons learned from that as well.
So love to come back for those on another episode.
Pierre: Yeah, one hundred percent. I think you know, the moral of the story is that, is it gonna be perfect? Yes. One day. Let’s start now. Let’s be pragmatic and enjoy the journey and we, we may make mistakes along the way. We’ll fix them. And it’s a journey that counts, right? And then we’ll have what we want at the end, but, don’t be too much in a hurry. Essentially, get the basics right and then build from that.
Angie: Well, if you’re just setting out in your data journey, I hope these help you in some way, prepare for some of the realities and, avoid the, common tracks traps for new players. If you’ve been through, data transformation yourself, we’d love to hear about your own experiences or data centers to add to ours so we don’t feel quite so alone. Share them with us. Share this episode with your colleagues and your friends, and we’ll see you next time.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Ravi Chandra and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: I was on the highway the other day and there was this billboard up there. I won’t call out any company names, but it was of a local IT shop and they had a picture of Donald Trump waving his finger and they had some words up there about, ‘don’t let Trump get his hands on your data’.

And I thought it’s exactly the kind of gaslighting data sovereignty BS that we want to myth bust in this session. And, Ravi’s gonna thankfully school us all on how to think about data sovereignty.

Ravi : Indeed.

Angie: So Ravi, maybe we can start off with this. Like who should be thinking about data sovereignty when we’re thinking about visitor attractions and data, like, whose job is it to worry about this stuff?

Ravi : Well. If you are leveraging data across your visitor traction or your business, and of course you should be right, given that data is a key ingredient to making great decisions, you should care or at least have some awareness about the implications, especially if you’re dealing with customer data.

And so naturally that’s a core function of traditional like government governance or info security teams. But in our experience, some of these personas can take relatively extreme positions in order to avoid risk. And it’s like if you choose to never take a flight, well, you’ll never be involved in an airplane crash.

Right? But flights are a very pragmatic choice, especially if you need to travel long distances like over the Atlantic Ocean. And I suspect there is many out there that would say, actually air travel is the safest mode of transport out of all of them. So all of this is to say is that awareness at the leadership and exec level is incredibly important in my opinion, because data use can correlate with incredible outcomes on the ground.

 And I think it’s really important to have that awareness in order to take a pragmatic position across the business as opposed to through just looking through a specific lens such as security.

Angie: Yeah, I always think that relationship between, and in this case, it’s kind of like that triangle, isn’t it? Between the business technology and sort of legal security risk, et cetera. It’s the business’s job to be the tension. To, and like you say, like you can choose not to get on the plane, but also you’ll never see the world. And the same is true with Data and it’s a business’s job to be the tension. I mean, some of the best lawyers and some of the best IT security experts that I’ve met in my life have been that, risk pragmatic kind of profile where they say, oh, you know, we can go to this extreme and be this dogmatic, but with this reality and this reality, these are your options and these are your choices and this is kind of how you can play it and the pros and cons. But for the most part, a lot of people in these roles are fairly, extremely risk adverse and present a zero tolerance view back to the executive, which is, unless you’ve kind of schooled yourself up to, to provide that tension, a really hard place to battle from.

Ravi : That’s exactly, and this is all about what makes data such a difficult topic. Because there’s so much misinformation and fearmongering out there, and it’s that natural tension because data is seen as a sort of, you know, this slightly geeky, deep technical space.

It’s difficult without having some awareness and confidence around data sovereignty to participate in those conversations. And I think leaders and execs at this level they do need to be at the table because pragmatism is super important at a holistic level.

And unlike a physical asset, digital assets like data they’re so easy to clone and store and each copy is subject to different rules depending on like the local jurisdiction and any sort of legal framework that’s applicable to, to all of those parties handling that data in between. And so this creates this incredibly complex supply chain, and many of those touch points are actually outside of your control.

And, sometimes even the best of us in governance and InfoSec don’t actually realize that they don’t know about all of the parties along the supply chain.

Angie: Yeah, so many different systems and so many different attributes and so many different people using them and. So many different applications and ways that the data can be sliced and diced. It’s almost impossible for those in the risk team to keep their arms around the whole lot, let alone understand it, a deep technical level if they’re not that place themselves.

Ravi : That’s right.

Angie: And maybe you could explain just for the grandmas amongst us, like me, what is the difference between data sovereignty versus data residency? Like, how should we be framing and thinking about where one ends and the other starts?

Ravi : Well, it’s actually really simple. Data residency, which you may or may not have heard of because I think it’s often forgotten, but data ‘residency’ refers to where data is actually physically stored. Data ‘sovereignty’ refers to who can legally access it. The complication is that this distinction is not well understood, and we’ve seen many of the customers that we interact with conflate these concepts and probably most concerning, they’re unsure of the real motivation behind the requirements that they’re asking about.

And, and often it’s because they’re just trying to tick a box that they’ve got from another part of the organization. So it really comes back to that awareness of the concepts at play.

Angie: It’s funny you say that, and I think this is such an important point, that you’re making here because in the lifetime of the Dexibit, I’ve had, I don’t know, hundreds of conversations about data ‘sovereignty’.

I have never ever heard a customer or a prospect used the word data ‘residency’, or the term data residency. And yet I think every single one of those conversations has been about data residency and not data sovereignty.

Ravi : I totally believe you because if this conflation between the two terms, so what I’m saying is that box might not make much sense if you don’t understand the difference between data residency and data sovereignty. So let me give all of the listeners out there an example to make this really clear. Dexibit, we are a software as a service. So we rely on the cloud and we store all of our data in the cloud.

Let’s say we choose to use the Amazon AWS cloud provider, and we choose the Sydney Australia Data Center region. What that means is that data residency is really straightforward. Our copy of your data is stored in Sydney, Australia, and remember that’s just our copy of your data, so we can’t speak to the data residency of other copies.

But now data sovereignty, that is really who can legally access it. It is a much more complex conversation. Obviously the copy that we store will be controlled by us and we will manage and restrict access to it. But it’s also under the Australian jurisdiction, given that it’s stored in Sydney. And here’s a really interesting thing because AWS is an American company, it is bound by the US Cloud Act, which creates a pathway for the US Federal Government to also access that data. And I think that’s a big thing that a lot of people are unaware of the US Cloud Act.

Angie: You know what’s hilarious? That billboard that was up on the highway as well as having a picture of Donald Trump, it also had, I still won’t say what the company was, but they did have Microsoft’s logo on that with ‘Microsoft certified partner’.

Even though they were sort of advertising about this sort of issue of gaslighting around data sovereignty or data residency, I’m getting the two mixed up again. They were in fact working with an international partner who is going to be subject to the Cloud Act, like you say.

Ravi : That’s super funny because I think the Cloud act actually originated due to a legal dispute between Microsoft and the United States government.

And my memory’s a bit hazy, but I believe the US government were trying to get Microsoft to provide data from this servers in Ireland, and they created this act to basically allow them to get access to that. So yeah, it’s been put in place so that, the US authorities can compel tech companies to provide data regardless of where it’s stored.

It also is supported by these bilateral exclusive agreements between countries, between the US and other countries. In order to streamline that process, but clearly its impact is significant. It’s completely reshaped how we even think about data sovereignty. Because US tech companies are almost always involved when it comes to the internet in general.

Angie: And that’s where we start to get into it, right? Like if you want to live in a world where your organization operates on the internet, or if you want to operate a technology strategy, which embraces software as a service of any kind, or cloud computing of any kind, in this day and age, let alone if you’re using data that’s coming out of Google Analytics or Meta or whatever, like you are already in this world. So it’s not a question of a binary in it or not in it. And this is where we come back to the risk profile of like, legitimately, how interested is the US federal government in intercepting your data? And the truth of the matter is probably not that interested. So are we all worrying about nothing?

Ravi : Well, I think so. Of course that’s my hot take. But to add some color to your point again, I’d love to walk through an example. So let’s say that you have an online review that a customer has made about your business and your business is based in New Zealand, and the customer’s posted that review on Google reviews

Angie: …publicly,

Ravi : publicly.

So who actually owns the content?

Angie: Google.

Ravi : No, it’s actually the customer. The customer owns that content, so as in the text of their review, but by posting it on Google, they have implicitly agreed to the terms and service of Google, which gives Google broad rights to the custody and control of the data and what that means through the implicit. In terms of service is that the customer has granted Google the permission to store process and use that content

Angie: exclusive, non-exclusive global rights or whatever they call them, license to content, right?

Ravi : I guess so. And so as the owner of the business, you are able to consume and access that data as per Google’s policies. But of course Google is still subject to the Cloud Act that we mentioned before. And also the stored Communications Act again use federal law, but the New Zealand law might still apply in this case, for example, in cases of like defamation or if, if PII or personal data was involved in the content of that review.

So to go back to your original question. Things are extremely complex and if the data originated in systems that reside in the US or a US tech company was involved anywhere along that supply chain, the pathways to fall that for the data to fall into US hands are obviously there. So it just shows how challenging it can be to truly be in control of your data sovereignty.

And I think going back to your point. Really taking a holistic approach to risk management, classic risk management, is the way to solve these problems.

Angie: Can you actually achieve immunity from US jurisdiction? In today’s day and age?

Ravi : There is little that we nor any provider can do to truly address data sovereignty concerns or avoid the wrath of the US Department of Justice, short of building locally without any piece of US cloud infrastructure. That means no Amazon, no Azure, no GCP, no Snowflake, Databricks, et cetera, and that still applies if you’re running a hybrid or an on-premise model.

Because the software, the control planes are often still residing and owned by the US company, the parent company. Many would probably still advocate for such an approach, but it’s gonna be hugely challenging in its own right and certainly expensive Worst case is actually that lack of awareness because you believe that you’re immune. You think that you’re immune, but you don’t realize you’ve got a small piece of key infrastructure that is still susceptible to the US Cloud Act. And so you’ve accomplished the worst of, of all worlds.

Angie: So it comes back to this key myth that location does not equal control.

Ravi : I think so, yes.

Angie: And so with all of this complexity and uncertainty, what would you say is your recommendation for our leaders out in visitor attractions who are having to, you know, have that debate internally with risk and technology and security having to make decisions and maybe ultimately hold responsibility with that, or needing to step up and take that responsibility as a result of the decision process. What do you suggest for them?

Ravi : My hot take is that you apply classic risk management techniques once you ignore the specific nature of data and the murky waters of cross border legislation. The important job is to understand the risks. At play, the types of risks, the severity, and ensure that you’ve got an acceptable management plan in place and most of the cultural organizations that we work with, there will always be experts to help the exec team through these challenges.

And while avoiding data risks at all costs might make their jobs easier. One, it might be that you’re actually already susceptible to risks and you don’t realize it like, you’re reliant on US origin sources, and two, avoiding data is unlikely to be part of a successful data strategy.

Angie: Ain’t that the truth.

Ravi : So as long as you’ve got a good solid risk management plan in place, you’ll probably end up in a really pragmatic and powerful position.

Angie: If anything, you could sort of cut off your nose to save your face at this point, like, you know, like if you’re avoiding using the cloud and software as a service to try and avoid all data risk, you’ll probably end up with some horrific on-prem system that’s subject to all sorts of security slackness and hasn’t stood up to the same rigor that some of the vendors would in the first place.

Ravi : We see that all the time. It’s been the driver for many, many technical decisions that I think might’ve made sense, but missed the bigger picture.

Angie: I used to work in, the telecommunications and before that, finance and banking industry. And one of the things we used to worry about when it came to data geography was actually the opposite.

For those who don’t know us. At Dexibit we are based out of New Zealand, hence the accents which is a land of milk and honey, earthquakes and volcanoes, and subject to the odd tsunami as well. Which makes it a interesting place to think about data reliability and when it comes to the worst of the worst.

And so one of the things that, the big banks and the telecommunications companies worried about back in the day when we all had these on-prem systems, was what would happen if the city of Auckland was no longer standing or the CBD was gone. And the building where we house these data centers that we used to have on site was no longer a thing.

And so we would refer to, you know, different geographies in the country to keep copies of this data in places that were a little bit further in land that didn’t get quite so many earthquakes and all the rest of it, and didn’t have as many volcanoes as the 54 we have in Auckland. But then we would also think about, well, what if the most of the country was overcome and whether we should keep a copy of our data in Australia or even further afield.

And this is kind of the opposite problem of what we’re talking about here, and we’ve almost swung the other way with thinking too hard about this risk of, who’s got access to our data that we can almost get back into this land of thinking about the risks of having data all in one place. But there’s also sort of that risk of avoiding the internet and avoiding SaaS.

 So we’ve almost come full circle on this. Like to go from a space where we’re subject to all of these risks of having data and too much in one place and too local to now having all of the benefits of cloud computing and software as a service and the digital world at our fingertips and feeling too exposed that way and trying to come back the other.

So I think all of the advice that you’ve given is fantastic on the sort of pragmatic balancing of risks. But when we come, to the heart of those, like what do the laws actually say in the jurisdictions of the countries of the western world that most visitor attractions that we talk to operate in?

Ravi: Yeah. Well, as far as I know, most, if not all countries have strong legal frameworks in place, especially around personal data. The big one is obviously the GDPR in the European Union and and the UK and Ireland. In Australia and New Zealand. We have the Privacy Act, which definitely covers similar territory and I know.

From memory that even middle Eastern countries like Saudi Arabia and the United Arab Emirates have very similar laws, the personal data protection laws. So what does this really mean? What does personal data and how does it differ from just data in general? Well, basically there are really strict rules around what you can do with personal data and specifically data that personally identifies someone.

So, for example, let’s say you sell a ticket, if you store alongside that ticket purchase, names, addresses, and phone numbers. Well, that is personally identifiable information. And so that could be used to identify people and build models around them unwittingly, and this is a no-no. However, when it comes to non-personal data in general, there are no country level restrictions around data residency or even data sovereignty, not as it applies to typical visitor attractions anyhow. One exception that I’m aware of is Saudi Arabia, which definitely has a strong emphasis on data localization.

So for sure, if you’re operating within Saudi Arabia, you’d be expected to have your data physically located in the country.

Angie: And I think this is a thing unfortunately for Saudi is like the way that these laws have been written. They’re forcing huge costs on the organizations and the Kingdom to meet with this.

And at the same time, the pragmatic realities of that are not there. AWS hasn’t finished building their data center yet in Saudi Arabia, and they won’t for several years yet, like. The Kingdom are putting down a very difficult law for some of these organizations to work with, and it forcing a huge amount of cost unnecessarily because of the way that the law’s been written. But this is how it is at the moment.

Ravi: That’s right. Of course, there is a lot of, a lot of money available in that part of the world.

Angie: This is also true.

Ravi: That is true. However, you know, in the rest of the Western world I think we have a pretty pragmatic, again, to use that word or overuse that word. I think we have a pretty pragmatic laws across the board.

Angie: Yeah. Speaking of pragmatism, so our approach at Dexibit has always been, you don’t need to know that it was Ravi and that his phone number is, I’m not gonna give this out live on air. But and the exact address of, of where he lives with his family, to deliver a great visitor experience decision set that is going to govern your organization.

You need to know that you had a visitor. You need to know whether they were a member. You need to know if they visited alone or with a group at what time and what they might’ve purchased. All of these sorts of analytical data points, but you don’t need to know the personally identifiable information to be able to make decent decisions that are delivering on insight to your team that are helping you with getting more visitors through the door getting them to engage and spend and be happy and come back and join as members. And so the aim is really to minimize the amount of data that you are collecting in the first place. To be responsible. And a lot of the laws call for minimization and then obviously consent and encryption and treating things well, as hot points. But then also to minimize your use of the information about Ravi and his family when they visit. And for the purposes of analytics, we can deal with everything but the personally identifiable information or the PII, if we’re in the US of that, that data set, whether it’s ticketing or membership or point of sale or email marketing or whatever.

So our approach at Dexibit has always been to strip out the PII. And we certainly have never dealt with PCI, so the credit card information, like you would in a point of sale system for payments.

So we are left with the business analytics and business information, and this is such an important point, I think because most regulations in most of these countries that we’re talking about are referring and prescribing things to the data sensitivity, rather than just a blanket geography rule for all data of all time.

And this is this point that, that Ravi’s getting at is that there’s a big difference between like, I got 15,000 visitors on this day and we sold this many adult tickets and this many people visited at 2 35. And we sold this many umbrellas ’cause it was raining. And here is this information about John and his CRM details that we keep in a separate system.

It also means that you can safely democratize this data and give access to this data, without worrying too much about it versus like some of the access to your CRM system where maybe you don’t want everybody to see like the high net worth list that you’ve got on your advancement team, or you don’t want everybody to be able to just export the phone numbers and email addresses and email ’em off to a friend.

So being able to have a really safe data set to be able to use for analytics purposes responsibly, that’s minimized, to be able to give access to people, I think’s a really important principle when you’re dealing with analytics as well.

Ravi: That’s absolutely right. By mitigating this risk, by simply not storing personal data, we comply by default.

And all of those second order benefits are huge. Being able to democratize that data and create that richer, richer experience for the consumers of that data. And so this is where when you start to put this down, put pen to paper and create that, that risk management plan, you realize that actually taking the approach that we’ve taken at Dexibit means that data sovereignty and data residency do not actually apply and matter for use cases that we are talking about.

Angie: Security sure as hell does. And we go to extreme lengths on that front. So we’ve got SOC 2 compliance and all the rest of it, encrypt all of the credentials that we get in from lots of systems. I know you and your team spend a huge amount of time worrying about security. 24 7, Ravi.

Ravi: That’s exactly right. We obviously encrypt all of our data at rest and during transit. What that means is that we’re predicted from security attacks like the, the man in the middle attack where somebody that can take control of your wifi network, for example, can sniff and see all of your data.

Or even if they say can break in and physically steal hard drives, all of that data is encrypted and secure and safe. And I think what’s, just going back to an earlier point that you made, Angie, we don’t, build any of these security or encryption systems from scratch, they’re actually really difficult to get right. And instead we largely use Amazon, our cloud provider primitives, which have been battle tested and approved and reviewed and audited. And so it’s an example of the flip side where utilizing the cloud gives us an advantage in benefits and risk management for the benefit of our customers

Angie: and actually safer.

Ravi: Exactly.

Angie: You know what’s funny? Of all of the customers that I’ve talked to, the ones that have given us, the hardest scrutiny around security. 9 times out of 10 are the ones that will accidentally send us the spreadsheet of members with their phone numbers via email that we have to very delicately go back and make sure that we’ve deleted every single copy. And also unfortunately, educate the customers’ stakeholder on what not to send via email. So, definitely the case that having this sort of secure set of data for everyone to work with and have access to is a really important part because sometimes, like you say, you can protect yourself from, was it sniffing? Did I hear the word sniffing? Yes. Sniffing on the wifi. This is a new term for me. And you can protect from, you know, the person who’s going to break in with the hammer and steal the hard drive. But sometimes it’s like the internal risks subconscious or unintentional. But, still a liability, all the same.

And so I think that gives us a beautiful wrap up, Ravi, thank you so much for the introduction to this topic.

I feel so much more confident about talking about the difference between data sovereignty and residency, the difference of where data is stored versus who has access to it in terms of the legal jurisdiction and that whole difference of location versus control. And, talking about the Cloud Act and balancing some of the realities and risks, but the pragmatic view of those. So thank you for taking us through that. Any last thoughts to leave us with?

Ravi: To sum up, I think data residency is actually a non-issue for most of our customers, and there are actually a lot of benefits to sticking to the cloud. Because there is so much more gains in terms of efficiency and performance.

True data sovereignty, on the other hand, is incredibly hard, and it’s unlikely that most organizations could actually weather a Black Swan event. At Dexibit, I believe we take a very pragmatic approach that really balances risk with operational efficiency to ensure that, every customer’s data is protected to a high level with security and encryption without compromising on service or experience, and ensuring that consumers end users can have access to that data in a really democratized way.

Angie: Because sovereignty or residency is not necessarily security is it? Security is so much more than the laws of who’s got access to your data and that’s what really counts at the end of the day. Like you say, service speed.

Innovation, price and cost and time and everything else. But security is really the thing that people are chasing here to make sure that they’re compliant with the laws, but they’re making good, sensible decisions. And so we just need to get pragmatic and interpret those laws correctly for our data realities.

Ravi: Absolutely.

Angie: Well, thanks very much. I’m gonna go and, drive past that billboard once more.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Ravi Chandra and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Ravi, tell us about this. You’re probably the best person in the world for me to ask this question. How hard is it to build a data product?

Ravi: Maybe the best way to answer this is first to zoom out a little bit. Why do we want a data product for the visitor attractions in the industry for our business? I think it’s really this recognition that data and insights, it’s critical to running a modern business and in order to sort of clear that bog and improve visibility so that as operators you can understand where the problems are, see the opportunities to improve performance.

And with that visibility at all levels of your organization, you are equipped to take better decisions. And through those better decisions, you can improve the impact that every individual can make. So I think it’s, we’ve all realized that data and insights are critical and to me it’s, they’re our leverage that we have as leaders.

There’s a great quote by Archimedes, if you give me a lever long enough and somewhere to stand, you can move the world.

And we will get very excited about that. And I think that’s why we’ve seen so much growth and interest in data, in recent times. However, there is a little of nuance to this and I think we’ve also seen sometimes organizations take this a little bit too far in overreach and they end up in this sort of quagmire.

They think they’re doing the data and insights thing, but actually what they’ve ended up doing is getting bogged down, worrying about, building rather than driving impact through insight and answers. And because this is what we do at Dexibit day in, day out, we have realized through hard for real world experience that it is actually really, really hard to build a great data product and deliver a fantastic data experience where users and leaders at in all parts of an organization can see how they can use it within their workflows, within their day-to-day to make an impact.

Angie: Yeah. And it’s no surprise is it that the research shows, I think Gartner says what 85% of big data projects fail and you can kind of see why, like, for us, it Dexibit but it’s our life’s work to produce a great data product. But it is, it’s tough. It’s a hard job!

Ravi: That’s right. And I think the challenge, that you face is that. Really what people want and what delivers value is that pot of gold at the end of the rainbow.
But to get that and to deliver that to chase the rainbow requires so much work. And it’s that tip of the iceberg problem where a lot of it is invisible and it’s unknown to the end user or the consumer. And that’s why I think it’s easy to get carried away. and not realize what goes into building a great data product and to make this really real and concrete.

A big part of what we do is spend a lot of effort in plumbing, basically connecting all the pipes to ensure that data is flowing from source to destination. Just like the pipes in your house that you never really stopped to question unless there’s something wrong. It probably took a lot of planning and effort to put them into place, and it’s a big part of, building a data product that often gets underestimated. Then on top of that, there is the performance. Is everything running fine? Is it fast to load a dashboard? Does everything arrive in your inbox at the time you expect it to? When you log in to look at the data, how long do you have to wait?

Is it go make a cup of coffee or is it instant so you can start digging into it? The performance is a big part of what we invest in, and we are constantly trying to improve that side of our product, because we think it, it plays a big role in democratizing. Data for everyday users in a big part of the user experience.
Because what that means is if you’ve built an in-house data solution and it takes 10 minutes to generate a report, it really affects how you choose to interact with data at an organizational level. One of the things I’ve noticed is that organizations are very malleable and they will adapt to what they have to work with, and they then become that they internalize what data means for that organization based on what they experience, and they just become used to it.

It’s hard to know if you’ve gone the build route, whether you are actually at the forefront of what’s possible. Or you are actually behind the curve and others are doing it much better, much more efficiently than you are, and you are missing out on all of that value and impact that could have been, available.

Angie: If it’s gonna take you two years to build something, by the time it’s all said and done, where you’ll be at, then by the time everybody else has leapfrog over top of your position of where you’re  planning for now. And it’s, funny you talk about, the performance thing. We get two types of customers who come and talk to us.

One is customers who have never had a data solution and they’re making that first time decision. The second is people who have tried or even have built their own data solution only to find that performance problem comes to bite them, or the innovation problem comes to bite them, or the cost problem comes to bite them and then they come back and say, Hey, it takes our, you know, our system, five minutes to generate a query and can you do it faster? Well, the reality is that our performance is more like one or two seconds to deliver the same result. So, it’s, yeah, I think they’re really real problems for people who are sitting out on this journey.

Ravi: And I think the problems don’t stop there. Once you’ve delivered that report, the next thing that you’ll almost certainly encounter if you want to get traction with data in your organization is the needs from a diverse set of stakeholders, all with their own questions, their own business questions to answer.

And one of the mantras we have at Dexibit is providing insight for any question. What that means when you’re building Euro, building it yourself is you often have a queue of requests that start to accumulate and how you respond to that in order to convert that into answers to feed the rest of your organization is actually quite a critical element that often gets overlooked.

Because you’re taking on so much more operational burden by building yourself. You’ve gotta keep all of that plumbing working, stop the leaks, think about performance and optimizations. But then on top of that, how do you find time to, to model and understand the domain that you are working with? And in order to answer, all of these different questions.

So for some real examples, you could have questions from. On the retail side of the business about, product sell through rates or come could come from marketing or around social media engagement. These are all wildly different business spaces, but they’re all part of a complex contemporary visitor attraction.

And if you have to model that every piece of data in order to build a report. It becomes a huge amount of work and these teams, they stop asking, and I think that’s the worst thing that can happen because you saturate your capacity that it turns people away from data insights. So it’s almost like the antithesis of the original goal that organizations start to trying to solve.

Angie: Yeah. If you’ve got one person in a corner office or in the basement. Doing the data for everybody else in a queue out their door of people with requests for, can you build me this, that, and the next thing? You’re, doing it wrong at that point, right? Like, we’re all about democratizing data and from our product that also means about self-service and, data literacy and supporting all of these sorts of things.

And we firmly believe that you’ve gotta have that to have the agility to make not only decisions on a real time basis, but to make the culture of it all work.

Ravi: That’s right. Have spent some time thinking about this problem. And what we’ve really come up with is, first of all, we’ve spent a lot of time in the industry speaking to customers, understanding their needs, and we have a very good understanding of the different domains within the business.

What we’ve tried to do is to bottle that secret source and embed it within our product, under the banner of what we call, our semantic layer. And that gives, most businesses a huge head start and leg up around what it means to be operating a business within the space and what their needs are in terms of data.

So on top of that. They can leverage what we built to then sprinkle in their secret source that’s unique to their business and customize our product so it meets their needs.

Angie: Yeah, that’s a really good point. And I think, in the visitor attraction sector, this problem is especially intense because they are really complex business models.

Your average visitor attraction. Sales tickets to the gate, maybe extras for exhibitions or events or, other experiences. And maybe they do tours and maybe they host weddings and maybe there’s corporate hire. And then on top of that, they’re running food and beverage and, retail and maybe a hotel even, some parking and everything else.

So they’re really complex when you start to bring all of these together. And then you layer membership maybe, or season passes and advancement and. What they’re doing online. And then maybe collection management got huge risk management to take on board and big operational and security teams. Like, it’s never ending.
And it’s different to running a shoe shop where you’re got a pair of shoes with a price and a data point that arises when you transact. And that’s about it. And so I think it’s a problem that’s especially felt by this industry.

Ravi: Absolutely. And I think it’s almost ironic because it’s that complexity that sometimes drives leaders to think that they are special and they do need a custom bespoke solution.

But actually in fact they really don’t, and they probably don’t have the resources and expertise in order to take that complexity. And realize that, so there is a spectrum, right? Between build versus buy because you could buy everything. You could buy something that’s customizable, you could be working from a bag of bits, some that you bought and some that you’ve built and be assembling things…

Angie: and essentially building…

Ravi: at that point, and essentially building at that point. Or you could even use off the shelf bits and be building everything from scratch. And I think with that nuance, there’s actually a range of solutions. So we’ve learned early on that businesses are complex and they need to be able to custom, we need to be able to customize our product.

And so we’ve baked that into our product experience. We are designed for you to plug in and bring your business rules, bring your special needs, and bring the obscure. Or the special data sets that’s unique to you and take it into our product rather than, have to do that from scratch at one end of the spectrum or say, no, we can’t support that at the other end of the spectrum.

Angie: Yeah, because thinking about all of those different domains that we were just talking about that, that you’d have to have that knowledge or be able to orchestrate that magic across that technical business barrier, which is one of the hardest parts of building technology. There’s also, then, when you get into the data space, there’s lots of different skill sets that you need, right?

Like there’s the Insights leader who can translate things into executive speak. There is the product manager who can kind of, keep a team on track and help execute vision down into operations. There’s the data engineers, the plumbers of the world if you like. The scientists who are experimenting and researching with different models, your analysts.

And so you’re talk, starting to talk about quite a big. Team overall of these different skill sets to build it up. And it’s quite easy to see how we’re not just talking about a six figure investment to, to build, we are talking about something in the realm of seven figures Plus when we start to get into all of these different areas.
Ravi: I think you’re right and you’re touching on the realities of what it means to do this. We know that, the Tran recently posted that there. A typical customer spends at least $300,000 per year just on their data warehouse technology, and that doesn’t include any of the labor costs to, to maintain that.

Angie: Is misleading with some of these, big players, they might sort of use the micro pricing when you’re looking at sort of $2 here for compute costs or something on a credit. But it adds up when you’re talking about the volume of queries and the data that you’re processing through some of these platforms.

Ravi: That’s exactly right. And to understand the nuance of how these. These pieces of infrastructure, data infrastructure come together. How they build, how to make the use of how to make the most of their performance and use them effectively and efficiently. It requires a lot of deep expertise and knowledge and comes forward with many unknown unknowns.
And it’s only really when you are knee deep in it that you start to, to see these challenges and gaps emerge data and insights. It seems to be an interesting space where it feels very easy to get started and if you’ve got people within your organization who are quite good with a spreadsheet or a little bit technical, you can see how it escalates from belief and with a bit of confidence.
You can see how it escalates into, like, we think we can do a bit more. We can take this on, but it’s. But organizations often sort of have this stunning Kruger effect, if you’ve heard of that, where you might think that things that you don’t know very much about appear to be easy, but you overestimate the effort in areas that you do know a lot about. And I think this is one of the classic pitfalls of the, to build versus buy decision.

Angie: And just to add to some of those costs that you were talking about before. When we’re talking about building out that whole team, I mean head of insights, we are talking what in the US north of 150,000 a year.
Product manager, maybe one forty data scientists, one forty data engineers, probably about that. Analyst, maybe 85 to a hundred. Like we’re starting to add up some very serious resources to be embarking on a project that we’ve got no guarantees at the end of, and a team that presumably have never come together before to do exactly this. So it’s all breaking new ground into white space, which is the hardest thing to do in technology.

Ravi: It absolutely is. And don’t get me wrong, I think it’s amazing to grow your team and take on more talented, people within the space. And I firmly believe that they could add a lot of value to your organization or any organization.

But I think what’s important is to ensure they’re steered in the right direction, working on problems that are valuable. And a part of that is using the best tools out there, not necessarily building your own bespoke tools, because that’s not going to unlock and drive value. And I think it’ll become hard to continue to argue for those budgets if you go down that path, spend two years to, to build. And don’t have those results to show for it.

Angie: And it’s, it also improves out in the numbers as well of the realities of the insides of some of these teams. Like I think embarking on a data project sounds. And feels very sexy from the outside. But get into the inside of it. And like you’re talking about data engineering being sort of the plumbing.

I had a trades person run at my house this morning, you know, unless there’s sort of a painter who’s. Leaving you with a beautiful house at the end of it where you can stand back and say, wow, that looks incredible. If it’s a plumber who comes in and fixes a pipe, I mean, it’s a very thankless job.

And data engineering, and keeping all of the things connected and all of the lights on and making sure nothing fails and cleaning up when it does. Is a very thankless job and like the average tenure of a data engineer on an in-house data project is under two years. It’s closer to one than it is two.

I think, overall in the states, some of the research shows that the average tenure for any data engineer is about 18 months. And it just goes to show like this is the reality of executing on some of these data projects, and that’s a real challenge. I think when we’re thinking about total cost of ownership, like there’s the time that it takes for you to get from zero to one and what you do beyond that, there’s the cost of all of these resources added up and all the different component parts, but then there’s also the risk.

There’s like the risk of will we make it, and then the risk of whether these people will be. Ones that stay with us through the course of, of the lifetime of the project. Even, you know, if it takes a couple of years to get there, that might be several generations of data engineers under those timeframes.

Ravi: That’s a real, very real risk. And with that, that turnover goes, the organizational intuition knowledge about a lot of these systems and about a lot of the plumbing. When you talk about plumbing it’s critical to keeping everything running. So it’s an underestimated and an undervalued risk, in my personal opinion.
One argument to mitigate that risk, which you see often is that there is a lot of, services and off the shelf connectors that can be used to avoid some of that plumbing. However, what we’ve experienced is that. They’re very general. And for our particular industry, a lot of the sources and systems are very bespoke and obscure and you just simply cannot find off the shelf connectors.

And often this is one of the ways where a build project starts to build steam because they can start with the easy stuff with some off the shelf connectors for Shopify. Or for Facebook for instance, very common. But then once it’s, once you get into the really hard problems of ticketing systems and football cameras and food and beverage systems and point of sale things [00:21:00] start to get a lot more tricky and complex, and that risk is not front loaded at all.

But it’s pushed at the back end of these projects, which is why they can somehow feel like they’re stalling. And I think that’s a failure mode that we’ve seen play out, a number of times, unfortunately.

Angie: Can we talk about one of the elephants in the room, which is, you know, that tech teams love to build?
I mean, you and I have had our careers in technology, so we. People who love to build things. And there is sort of two pathways when you get into a technology career where you can work in a product company. And build a product. You can work in a service company and essentially do consulting, or you can go in-house and you are constantly faced with this pull between buying things and watching other people build them or building them yourself, which is a very big temptation.
I mean. How do you wrangle with that yourself and for your own team? Because even within the software that we do build, there’s lots of decisions that we make to buy things or build things with the various components that make up that product.

Ravi: I’m an engineer and in my heart of hearts, I love to build things as well. So I’ve been bitten by this. Bug, so to speak. But I’ve spent a bit of time in, in academia as well, and one of the quotes that’s really stood out to me is, academics often to talk about standing on the shoulders of giants. And I really like that mindset to think about what we are doing in the engineering and IT space now.

And data and insights. Just because you’re not starting from scratch, it doesn’t mean that you’re not able to contribute in a meaningful way. I think it’s really just understanding and being cognizant of what you’re building and whether it is the right thing to be building and to be very honest, we’ve made mistakes at Dexibit as well.

I think there are a few decisions that we’ve taken that we now regret where we’ve. We’ve been thinking about the build versus buy spectrum and we’ve, taken a decision that we now regret, for example, to make this really concrete, we chose to build our authentication and authorization service within our product, and that’s largely under the covers for most of our users, but it’s responsible for being able to log in, being able to access your data and not having it accessed by other people who shouldn’t be able to. And when we were evaluating our needs, it felt like they were special and we could do better to build this in-house. What we’ve realized now is actually, this is really hard.

We have to deal with the after effects years down the track because now we can’t even remove it from our tech stack. It is so ingrained. The job and the effort required to remove it is actually very high. So we’re stuck with it, so to speak, but every day, every week, every budget. We have to account a certain amount for its maintenance and for the frustration that the engineers have to deal with in order to deliver additional value for our users and for our customers.

So I think if we had a time machine, we would definitely go back and change that decision. However, to be fair, you know, when we think about how this decision got made in the first place, it wasn’t due to any malice. But just genuinely not taking into account the total cost of ownership of the decision, the ramification that the decision would have across the rest of the product, and probably just underestimating our own knowledge of the space.

So we encountered many challenges, which I. Which for us at the time were unknown unknowns. That basically means we didn’t know that problems existed. We hadn’t encountered them, and we didn’t have the experience to draw from, to realize that there were actually things we didn’t know. We didn’t know.

We didn’t know those So that was one example. I can probably give you another one where, we’ve probably made I think, a better decision. So previously in our product, we used to do a lot of natural language processing. We ingest, customer reviews, feedback forms and surveys.

And, a couple of years ago we had our own data pipelines using machine learning and natural language processing techniques to break down, customer’s feedback into words and sentences and analyze sentiment and so on and so forth. At that time, it really was a state of the art and a great solution, but then came along, GPT and large language models and that really changed the entire, shape of what it meant to do this kind of work.

And so we pivoted towards buying. We realized that actually this was very hard for us to compete with. Actually we couldn’t add any additional value on top of what, was on the market. So it’s where we’re sort of learning from our mistakes, so to speak, and thinking about the builder versus buy decision through different lens and the entire lifetime of that product or that initiative, as opposed to just the build cost.

Angie: Yeah, it’s funny you talk about one of my biggest regrets and then one of our biggest wins at the same time, with those two stories. And I think it goes, it speaks to that sunk cost fallacy as well of like, it would be easy to look at that and say, well, you know, we’ve spent years developing this particular part of the product that dealt with freeform visitor feedback and that used all of this technology that we’d built out.
And it’s quite the swallow to, take that on the chin and walk away from it and start afresh with something that then overtakes it quite quickly. So it feels bad and good at the same time. I think, one of the things that was coming to me as you were talking about the identity management example, was a guy I used to work for at Hewlett Packard.

He would say “You should only build when it’s core to your mission, when it’s part of your unique sales proposition as an organization.” And for me in a visitor attraction that is things that are inherently part of the visitor experience. So if I’m Disney, for example, and I’ve got my magic band. That for me is an example of a visitor attraction, example where building the technology kind of makes sense because it’s something very unique to Disney, very core to its customer or visitor experience.

But for us at Dexibit being able to log in is not something that’s unique. It might be a necessity to support our customer’s experience, but it’s not the core of it. So getting really specific about how you sort of navigate that strategic decision. I think really comes to, to help, make that decision of where you buy versus build.

But it is a really difficult one, I feel to, to push back on. What advice would you have for people like me who are. Not engineers themselves don’t have the knowledge to understand, or the foresight to be able to know just how extensive a build was gonna be, how long running its ramifications would be down the road.

How do you push back or navigate that kind of decision space while still trusting your technical team?

Ravi: I think if you consider yourself to be a visitor centric organization, which I think a lot of you listening probably do, I imagine you would ask yourself, what value is this going to bring to the visitor?

And really think about, where your build initiative fits in and. Where instead you might be able to build something that sits on top of the shoulders of giants, for instance. Something like the dexibit and how you can extract even more value that’s unique and a unique proposition to, to your visitors and your business. One of the great quotes I’ve learned over the time is from a blogger called John Cook.

And a lot of leaders tend to think of building a software system as like, playing with Lego. And all you need to do is just. Click in different blocks of Lego together and you’re done. But in reality, and this is this fantastic quote, integrating two software systems is usually more like performing a heart transplant than hugging in lego.
If there’s a close enough match and the people doing it have enough skill. It’s possible, but the pieces don’t fit together. Trivially. And what’s worse? Failure is often never immediate, but it’s takes some signs before you see the rejection. And I think it’s an extremely apt quote and something that’s realized by a lot of organizations that go down the build path for the wrong reasons or with a lack of that knowledge around the total cost of ownership. And what this means in the longer term.

Angie: Yeah. I think one of the other things that I found tricky in that decision was, which I hear a lot from visitor attractions when they’re making a data build versus buy solution is, it’s really easy to fall into that trap of, but we have this one special thing. And to feel very unique in that space.

Oh. But we’re a museum that has special exhibitions and general admission, and we charge ’em as separate tickets or something. Or we’re a location based experience, but we do tours and they depart every 15 minutes and feeling like those are unique things and often that they’re not. And often there are great ways to work with problems like those.

For us in that identity management experience, it was, oh, but we have multi-tenant customers. And that was like the requirement that we hung our hat on and decided to build versus buy. What would be some of the things that you would challenge? A tech team with if they’re sort of coming to you with that one special.
But what about this thing? Often these things are, the little use case that’s quite rare to, to encounter too. So they’re not necessarily, the thing that the team comes across every day.

Ravi: I think it’s really just pushing the team to really think through the solution space.

And ask themselves whether there are other avenues to solving the problem, that can sort of mitigate that requirement. And I think that’s what we didn’t do. In that example, we landed on a very specific solution that didn’t exist in what was off the shelf. And we’d concluded that therefore we needed to build that piece of technology.

However, if we perhaps reframed the problem, we could have arrived at the same outcome using a plethora of choices of the shelf.

Angie: Yeah, it’s funny, I often find that you don’t know what you need to know until you get to that point that you need to know it. And it’s like if you sort of resolve the other 99% of the solution, then that 1% that you’re hanging your hat on saying, oh, but this is special because this, then becomes clear to you at that point because you have those shoulders that you’re standing on, that, that view that’s different from the top versus when you’re starting with a blank page and saying, oh, but this special thing, it becomes this mountain that you’ve gotta climb in this big edge case everybody focuses on. And that can then become quite sidetracked.

Ravi: I, I think so. To be honest with you. Another part of this was I feel like there was a disconnect between. How our engineering team, our tech team, understood the needs versus what the needs actually were from the business and customer side. And, we could probably have done a better job of seeing each other’s different perspectives to realize that they were actually probably quite different needs, but the way they were interpreted seem to result in this very special case.

Angie: …and that’s such a common problem, isn’t it? Especially in this example that we’re talking about where we’ve got a, maybe a tech and digital team who are perhaps quite departed from the realities of being on the ground and visitor services, or being embedded in finance or out with marketing, running campaigns like because of the diversity of the stakeholders and all of their use cases and the business domain knowledge that’s gotta go into all of these problems. Like that becomes a really compounding issue to maintain that bridge between technology and business.

Ravi: Exactly. And. We’ve seen this, I’ve seen this a lot where, sometimes the tech team and the engineers, they’re focused on moving numbers around. And so as long as a number appears on your screen or in the report, it feels like everything’s working to them.
But the business users who are actually looking at their report to them, although there are numbers there, they actually don’t make any sense because they’re so far away from what they expected. The business metrics that matter and when you’re not connected and on the same wavelength, it leads to these perverse decisions and misunderstandings.

Angie: I’ve got a couple of questions here from, some of our listeners. I’ve got one here from Kevin, the head of visitor services at a mid-sized history museum in Ohio. Hi Kevin. He says, “We’ve been leaning on spreadsheets forever. Now, there’s a push from leadership to in quote, get serious about data. The tech team in IT want to build us a custom dashboard in-house. I’m worried it’ll be months before we see anything usable. How do I push back without sounding anti progress?”

Ravi: Hi Kevin. That is quite a predicament that you’re in. I think you’re probably right to be worried and concerned. My suggestion would be to talk to your business stakeholders and get a better understanding of what value they get from your spreadsheet and what’s missing, and ensure that they look beyond just the build your own, do it DIY solution space, and see what’s out there on the market. What can be used. What you can really use as a lever to drive more impact. Because I think for example, with Dexibit in your hands, you will have so much more agility that you can do everything that your in-house tech team wants to do, but in a matter of days, and not just for this one data set that you’re talking about, but you have the ability to work with, plug and play integrations, but also upload your own bespoke data sets and spreadsheets and create all of those dashboards and reports.

Angie: Yeah, I would echo what Ravi said. You are right Kevin. It will take months before you see anything usable. Maybe a little bit longer. My advice in this situation would be, if you’re the head of visitor services.
You don’t need to be passive in the technology making experience decision experience, like, best case that should at least be a partnership between you and technology or the IT team. But. You know, if it’s not that equal partnership where you’re making that decision jointly, and it’s not about, in your words, what the IT team wants, I mean, at the end of the day, you are the person, you are the team who will be making the decisions based off this data and this data solution. So I would suggest to you that’s your decision to make. So don’t be afraid to step into that leadership, into that space and lead the decision of are we building, are we buying, and if we are buying what and why?
And. Provide a framework for your team and the IT team to work together to make those decisions and be able to challenge and push and pull within that framework to lead the team to make the right call. Rather than saying hands up in the air, this is the it team’s decision. And we’re just gonna go with whatever they want.

So that, that would be my suggestion. I know it’s tricky when it comes down to whose budget is it coming out of. But hopefully there is also that sense within the wider leadership team of who are the core stakeholders who are leading in this space.

And we have another one here from Leila, a marketing manager at a science center in Canada looking at buying a COTS data solution. So I presume that means commercial off the shelf data solution. “I’m struggling to compare the cost to what we already do with our ticketing systems reporting. Is there a framework to help non-techies understand the real cost of building versus buying? That’s a tricky one. I would jump in there. With the fact that one of the things we talked about today was lots of different data coming from lots of different places. And your ticketing analytics or ticketing reporting that’s in that system is just one piece of that puzzle. And there are lots of different data points and metrics or key performance indicators that you need to run your visitor attraction.
And let’s take one, like revenue for example. To get a revenue out. It’s not just gonna be ticketing. We’re talking about food and beverage. We’re talking about retail. We maybe wanna look at something like average revenue per visit and maybe we recognize visitation of footfall. Maybe we’ve got a food and beverage joint venture revenue share partnership with a local cafe operator. And so we need to take into consideration that that split as well. So we are talking about lots of different data sources already just for this one, KPI and lots of different automation requirements and lots of different things. Ravi mentioned all the stuff that’s happening under the hood in terms of transformations and business rules and so forth. As well as all of that coming together, plus we’re talking about all of those things of, and how do you visualize this and, you know, do we wanna look at per cap by day of the week or per cap when it’s rainy versus windy, and all of these sorts of things. So this is a much bigger problem than saying, how many tickets did I sell today? Out of your ticketing solution. And I would say the same is true for pretty much every system that you work with. Like Google Analytics, for example. Great place to go to get data about your website. Facebook. You can go and pull some data out of there as well. But what you end up with is that problem of like copying and pasting data into spreadsheets and circulating them in reports and lots of effort involved in data admin. And time and that’s all energy that’s not being spent on making great decisions. What would you add to that, Ravi?
Ravi: I can’t add anything more to that. I think you’ve answered that question extremely well. 

Angie: maybe you could help me out with this one. Raj from a theme pack operator in Dubai. He says, “We’ve in invested in an internal data lake and we’ve got a strong engineering team in house, but I’m under pressure to demonstrate faster return. How do you balance what you’ve already built with the appeal of buying something that could plug in faster?”

Ravi: I think it’s a really great question to ask because it shows you’re really thinking pragmatically about how to deliver value and not just about working on a project because it’s fun and cool. There’s actually quite [00:42:00] a lot of different ways to integrate and in-house with an off the shelf solution. So for us at Dexibit we do this quite often because again, we can leverage the work that’s already been done to good effect and allow your team to focus on adding value and building on top of the combined software. So we can integrate with a lot of standard data warehouses.
Such as Databricks and BigQuery and Snowflake or SQL Server, and we can leverage all of that work. We can over time slowly migrate away from that. So then you are no longer burdened with the maintenance and the operational expenditure that comes along with keeping the lights on and keeping that performing well.
Or we can choose to leave it in place and continue to build new in our product. So there’s quite a lot of different pathways that you can take, and the best is the best way forward is really just to have a conversation with your chosen vendor.

Angie: Nice. Well, if you like the show, come and find us at Dexibit.com or send us your questions at info@dexibit.com.

Thanks for listening to the Data Diaries so until next time, this is Dexibit. Thanks, Ravi.

Ravi: Thank you.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

If you want go from gut feel to insight inspired, this is the Data Diaries with your hosts from Dexibit, Pierre Perez and Angie Judge. The best podcast for visitor attraction leaders passionate about data and AI. This episode is brought to you by Dexibit. We provide data analytics and AI software specifically for visitor attractions so you can reduce total time to insight and total cost of ownership while democratizing data and improving your team’s agility. Here comes the show!

Angie: Pierre. What is happening to the world? Tariffs, tourism, takeovers. It’s been a real mixed bag the past year for visitor attractions when it comes to visitation and growth. It’s a jungle out there.

Pierre: Absolutely. Global data has been all over the show, especially since 2024, right? We’ve seen a huge change in behavior in 2024 and. Seems to be the same for 2025 so far. We’ll dive a little bit into that later on because we have some really cool benchmark data to look at. It has been a very different year so far.

Angie: To put this into context, if we wind the clock back to 2024, globally, visitation only grew the whole year, year on year, from 2023 to ’24, only by 5%. That was down from 30% the year prior. It was actually lower in the Northern hemisphere down to 3%, which was dropping from 16% the year prior. So 2024 already was kind of flat. I mean, we don’t expect the industry to grow at 30% year in year. Right? Like that was a, that was still a bit of pandemic recovery. We are talking about ’22 to ’23 at that point. So ’23 to ’24 was never gonna be pulling double digit numbers, but 5% felt [00:02:00] a bit flat and a lot of that growth was banked up into Q1. We saw some good results. Everything was off to an amazing start. January, February, March, by April, we had a real dip and then had a soft summer in the northern hemisphere and the second half of the year just really struggled to get off the ground.

Pierre: Yeah, absolutely. There was this saying everywhere on social media survive until 2025 – 2024 was looking a little bit green. But, you know, bear in mind, 2023 in a lot of regions, people were recording their best year ever. Right. We, I was, I remember being in, in Europe in 2023, we had an amazing summer and visit attractions were performing extremely well. It didn’t sort of carry through 2024. 2024 in my opinion, was the first normal year after the pandemic, right? This is where like everything is back to normal. Now, let’s have a look at how we perform in 2024.
This is what people that we work with are doing what worked, what didn’t work? Can we use levers to amplify what work in 2024 in 2025? And this is what most of the conversations are right now with people that we work with.

Angie: And there was a couple of reasons for some of the stuff in 24. I remember April, we had some changes around holidays, number of weekends. Tell me more about that.

Pierre: Yeah, it’s always a good one to, to look at. We usually, we sometimes are guilty also to look at data very zoomed in, which is usually done a month, granularity, right? And we looking at, we look at our numbers for the month and we say, Hey, look, we overperform against last year, we underperform against last year, et cetera, on a monthly basis.

What we do need to do on top of that is zoom out a little bit and understand how the specific month of each year is shaped against the same month last year. You’ve mentioned an extra weekend, or, one day of weekend last this year against last year can have a huge impact in your numbers, right?

So zooming out to understand that. If we talk us, we have, you know, holidays such as spring break that I’m never usually, on the same month or same time of the month each year. So that can also play a huge fact into the deltas that we are seeing when we are analyzing year on year performance and a monthly granularity.

Angie: Yeah, and I remember, Easter has shifted around. It was at the tail end of March last year, which gave us this really great booster March in 2024 where everybody thought the year was going exceptionally well. But then of course April down on the year prior, because that’s where Easter had fallen previously this year.

We’ve got Easter back in April again, and spring break. Let’s have a look at the numbers for 2025, we’ve got January down 2%, February down 10%, March down 11%, or actually for North America, just down 9%. So we’ve seen the flip of the coin here. If we flip back to 2024, we had, north America behind at 3% versus 5% for year on year growth across the year. So this year so far, we’ve got North America. Although negative figures like everyone else, they are actually ahead of the pack, down just 9% versus 11% for everyone else in March. But this year we’ve had a few weird things to contend with, right? It’s been a year of global events.

Pierre: It has been a year of global events and external factors like that do play a role in visitation figures. Right. Are we talking about domestic tourism, international tourism, et cetera. So there’s been a lot of different events that have been impacting visitation, this year so far.

Angie: Yeah, we’ve had, in the first few months of the year, we had one of the biggest cold snaps in recent history in the east coast of the US. Multiple snow day closures for a lot of locations and in LA of course, sadly, the LA fires, which closed many venues and continues on to have some impacts. Even now we’re recording this in what, May 25 we’re seeing still some impacts to tourism in la. We had, of course inauguration in dc and state funeral, which, impacted closures for those days and also has impacted, visitation somewhat, positively and negatively in some [00:07:00] spaces. Sadly plane crashes in DC and Philly. Having an impact on visitation, so quite unusual things coming out this year that have maybe had a say on those results.

Pierre: It is all linked together. Absolutely. And it’s hard to, identify exactly what may be causing, visitation fluctuation, but as you mentioned, it is absolutely a combination of events that has impacted visitation so far.

Angie: So this data is coming from Dexibit’s customers. We love working with this data. This is a very unique industry benchmark. First of all, it’s daily and granularity. Secondly, it’s real time in monitoring how the industry is going. That’s what makes it so unique. The only other data that we can refer back to is publicly available, published data from publicly traded commercial companies, from publicly published nonprofits who are putting their annual visitation so forth out there. So it’s really unique to be able to have this aggregate look at how the industry is performing. But if we, so we otherwise have to wait for what? 15, 18 months to get some results out for rest of industry, so the last data we have is actually all the way back to 2023 from the rest of the sector, where their public reports have been put out. And the year on year growth that the rest of the industry reported in 2023 was only 6%.

Keeping in mind that Dexibit’s customers in 2023 recorded growth rates on average of 30% in that year. So if they’re sitting at 6% versus 30 in ’23. We saw 5% from our customers on average last year, and this year we’re seeing negative. We can actually expect that the rest of the industry is somewhat behind those figures. Again, any guesses on why our customers outperform rest of industry when it comes to visitation growth?

Pierre: Yes. Are there educated guesses? Maybe less so. There’s a few theories out there. One is, customers are working with us for a reason, that they pay close attention to their data and they want to democratize the data across different departments, right? That means all the way down to the curator or your exhibitions to understand what is attracting visitors to your museum, to your zoos, to their aquarium, et cetera, et cetera. They’re also really conscious about pricing. If they do charge for, admission, which is another topic that we benchmark on for another episode, but they pay very close attention to how they’re performing and also how other people are performing. This helps them to make better decisions.

Angie: What do you think people are happy with as a growth rate?

Pierre: It’s a tough question. It’s how long is a piece of string really? Right? It depends on the department, I’m talking, you know, membership, retail, visitor experience and all of that. So when we talk about growth, and here for this specific context, we are only talking about visitation growth, right?

There’s also a caveat here in term of the type of attraction we’re talking about established versus fairly new, so the expectations will be different. Based on, how long this attraction has been running, right now in established attraction, I’d say, a yearly growth rates are of between five to 10% is sort of expected.

And I’m curious to see if you, if you concur or if you, have different conversation with people that you talk to. When you talk to, a new venue, these numbers are always in the double digits, right? Year on year.

Angie: Yeah, I think if you’ve done a, a really significant redevelopment or a blockbuster exhibition, you’d be expecting a minimum of 10, 30% plus on your growth rate. But if we are talking about, a new build, it’s different again, given that they don’t have a baseline to come from. Actually, typically we see the reverse in a new build, typically their first year is their best year. Second year is slightly behind. Third year, they tend to see a drop. As, you know, everybody who’s going to visit would’ve visited once. And then it’s about attracting, repeat and tourist, and new audiences. If we’re talking about an established attraction, I would agree with you. With a caveat that I think five to 10% is great. I think in terms of sustainable annual growth for an established attraction, people should be happy with around that two to 6% mark, would be my pick. So actually when we look at last year as result, although it was really bumpy through the year, which makes it a hard year. Actually the overall figure of 5% is not too bad if we’re sort of putting that in the context of that, that two to 6%, if [00:12:00] we were to look at it this through a business lens, your average sort of, small, mid-sized business is usually happy with something north of 10%, established companies like to sit five to 15% Nonprofits in that five to 15% mark as well. So yeah, I totally agree with you. Depends on the museum or the visitor attractions’ age, depends on what department and metric we’re talking about. Yeah, I would shoot for, if you’re going outside the two to 6% range, have a good reason why.
Pierre: I’m gonna have a question for you as well. Our mission is to democratize data in visitor attractions, right? We want to break down silos. Do you think the democratization of a visit to attraction in term of. You know, we’ve, we’ve had firsthand experience of people with no experience in visitor attraction before are building visitor attractions right now, right? Such as, family, entertainment places, one of the aspects that I’m curious to see, have we seen a growth in the number of venues that are out there? Because that will explain why also the visitation growth is not as big as what it was in the previous year, if you have more places to choose from to spend your time, the likelihood of guests returning to the same places is lower

Angie: Possibly. There’s definitely a lot of competitive activity, vying for a visitor’s attention, particularly in certain cities, like New York and, and so forth. LA. London, Singapore. But, I think that some of that competitive tension also comes from outside the industry, and in particular with our cell phones, you know, with the Tiktoks and the Netflixes of the world as well.

You know, when the family decides what to do on a Saturday morning, like peeling the kids away from a screen is half the battle. And then we get into the, and what do we do, once we leave the house. So I think that definitely,, yeah, that com competition is something to think about on all fronts. For sure. What do you reckon is easier to grow, visitation, attendance, revenue, or membership?

Pierre: That’s a very good question. I feel like revenue would be one of the easiest to grow, because you can simply put your prices up to a degree, without upsetting anyone dramatically. There’s a few levels that you can pull that are low hanging fruits, in my opinion, that will increase revenue.

On the visitation side, logistically and strategically, it’s a lot more complicated to lift, right? You’re talking organizing exhibition, which is not, you know, it’s not a two weeks project, right? It’s, it takes an enormous amount of time , and resources to organize. And that’s what you’re gonna need to increase visitation.
It’s gonna take special events, it’s gonna take festivals, it’s gonna take something new. Really drive people, were talking about social media earlier. Social media has new content very frequently, and this is I guess why people engage with it so much. It’s the same thing here, that if you want to drive visitation substantially, you need to have that fresh content in front of people to prompt them to come to you.

Angie: Yeah, absolutely. I would agree with that. I think it’s harder to get another person in the door than it is to get somebody who’s already there to spend more, do more. Even it’s harder to get a new member than it is to get an existing member to come back that one more time, or do a bit more the next time that they come.

When we look at the cost of servicing a visit, the visitor acquisition costs, the marketing dollars we have to spend to get that person to come to the attraction in the first place is one of the higher parts of the cost versus, servicing that visit once they are there. So yeah, I would definitely agree with you. I think if you wanna improve performance in these slim years going for improving your per cap with onsite spend, with ticket price, with auxiliary spend, that’s where the easier wins are. We’ve seen that in the publicly listed companies too.

Right? Visitation was flat or down , but revenue was up. They were getting more out of their visits, which is cool to see. Still a squeeze on the profit margins with rising cost, but great to see the growth.

Pierre: That was my next point, is that an increase in revenue doesn’t mean an increase in your margins or your profit. As we’ve seen, again, we talked about external events that are impacting visitation. The same goes on here with external event impacting potential cost of goods at retail stores, but also on the F and B sector.

Like things have been more expensive to buy for cafes and restaurants on sites, which means they need to offset that cost to the customers, which means yes, your revenue is growing, but it’s growing as a result of your cost increasing, not necessarily people spending extra. And I think that’s a different, topic for another episode. But this is also what I like to see is that if your revenue increases, what is it caused by? Is it because the average transaction has gone up? Is it because the basket size has gone up? And then you look at your margin and so on.

So, yes, revenue is easier to, grow than visitation, but you can also do certain activities to increase visitation, for you. Yeah.

Angie: Yeah. That’s gonna be the big question on everybody’s lips this year is the impact of tariffs, especially in the retail store. Like you say in food and beverage, even in those new locations who are trying to get their construction projects finished and have got equipment and facilities and things sitting at the border.

And looking at those publicly listed visitor attractions too, they haven’t, a lot of them haven’t yet published their full results for the year, last year. But what they are sort of all setting shareholder expectation around the theme of demand moderation in 2025. If we look back at their quarterlies that they were releasing, pretty much Six Flags was the only anomaly, reporting what looked to be about 3% growth with their merger, that they had. But everybody else, again, quite quite soft.
I wanna turn now and talk a little bit about tourism. We had US international tourism sitting at about 31% growth from in 2023 it was sitting at 66 million. Moved up to 72 million in ’24, not quite at pre pandemic levels of 79, although is projected to, to hit a record break in next year with America’s two 50 anniversary. But I know Oxford Tourism Economics came out and projected an adjustment down to as low as minus 9%, which everybody was scoffing at, but they’re indicating that the March actuals have come in just a touch under 12%, which, if they’re right, 12% negative growth, if they’re right, is a huge impact. If we look at some of the big visitor origin for US, international tourism, Canada, Mexico, China, Canadian entries were down 32% in March, according to Canada. Air Canada has actually got to the point of producing its flight volume and at one point Trudeau was telling his citizens to travel at home. This is really gonna be one of the big stories to follow for visitation in 2025 is international tourism.
Pierre: Absolutely. You know, despite that, despite the Canada entries being down, what we’ve seen is that domestic tourism in the US was actually really healthy. Especially in Washington DC where we saw a few museums really benefited from that local or hyper-local crowd coming and supporting them, and going to these venues, so that, that domestic tourism was looking pretty good.

Angie: Yeah, it’s interesting, Bank of America put out some figures of domestic tourism. So not looking at like local, hyper-local travel, but more, further afield, domestic tourism numbers in the US were sitting at 5% growth, 2023; 8% growth. 2024. Bank of America are saying credit card spending, electronic spending, down 2.5% in March, for lodging accommodation, and down 6% for air. So I think, whilst we’re seeing that sort of boom, especially in areas like DC on the locals and the hyper locals, perhaps those coming from further afield, like maybe people are less, less likely to fly, more likely to drive great for drive cities like, the DC Metro area, New York, la et cetera.

Maybe going to hurt a little bit. More for cities that people have to fly in, to visit.

Pierre: And that’s interesting to, to see, right? I guess you will expect locals not needing. Lodging or air travel as you mentioned. So let’s keep an eye on these numbers. We are, usually, at a zip code level when we, look at origin of the guest, and what we’ve seen is that the zip codes immediately surrounding venues, have been performing pretty well, in DC.

Angie: Yeah. And if we zoom out a little bit more in the world, I’m really curious to see how this tourism situation’s gonna play out for other countries. I mean, maybe one country’s loss. It will be another one’s gain. I don’t know how that’s gonna play out for our Canadian venues. For their domestic tourists or some of our other, you know, whether Europe might benefit a little bit from those that might be diverting travel from elsewhere. I know regionally like countries like Saudi, Qatar in the Middle East, leading on tourism growth because they’re coming from you know, a pretty low starting point. And same with some of Central America, and some of the cheaper just destinations in Europe performing really well. So I’d be curious to see how all of that plays out in our big cities around the world.
Pierre: Absolutely. I’ve been hearing some amazing numbers from Japan as well recently with a huge amount of international tourists, flocking to Japan right now to take advantage of the currency and the yen being so low. So there will be, I think, some really interesting numbers coming from Japan for ’24, ’25.
Angie: What’s your pick for what America two fifty is gonna do next year?

Pierre: I think, it’d be a great thing, right? Isn’t it? The FIFA World Cup as well. Then we had the LA Olympics in 2028 on the back of that as well, two years after that. So, I think it’s gonna be a, an impressive year. I mean, I know there’s a lot of these infrastructures and a lot of planning around that.

So I think it’s gonna be a huge year ahead.

Angie: Yeah, definitely for, East Coast. I think, DC is an obvious pick. Philly probably, I know Philly are also hosting some fifa, New York, new York’s planning some really cool events, I think, some of the sailboat, regattas and things like that for two 50. But yeah, I’m curious about what it will do in other spots.

Like in LA or San Francisco where there we’ll see quite the same impact on visitation for visitor attractions. It might be quite dependent on what their public programming is and how it sort of ties in with what city officials are doing and things like that. It’s really interesting to see how that plays out.

Pierre: I think so, and also interesting. We should be seeing some of these numbers very early on. Something that we’ve noticed in 2024 and 2025, but the shift. Of how far in advance people were booking to come to the venue or even the channel that they were using before they were coming to an attraction.

We used to see right after COVID a lot of people booking online and, planning their trip a little bit. Further ahead on what we are right now. We’re seeing a lot of onsite tickets being sold right now and all people being a lot more impromptu with their visits. So I’d be interesting to know what these big events due to that book in lead time that we usually look at. And I assume these numbers will be, started to be impacted, towards the second half of this year.

Angie: Hopefully we see booking lead time picking up a bit ’cause it’s been falling the last few years since the height of COVID. Definitely helps our attractions when they have a little bit more predictability and who they know is going to come.

So if you’re in Dexibit, pull out your benchmark search benchmarks in your library. You’ve got some great data sets in there for visitation growth, and much, much more. I always find, I don’t know about you Pierre, but I love walking through benchmarks with visitor attractions because you get that reaction of. It’s not just us. That sort of validation, of is it me or is it something else? Is it the world? I think that can be really good in both scenarios. Like when things aren’t going quite so well, it can be really comforting to have that sort of check. To be like, oh, this is actually a common experience. But also when things are going really well, it is also that nice check to know, to pat yourself on the back and give the team a high five, and recognize when things are above performance. Benchmarks are a great point to put into context how things are going for you and your team.

Pierre: And talking about benchmarks. I love that we talk about visitation. In another episode we can maybe talk about pricing, but also how are people feeling when they come to these attractions, right? Has the sentiment and the emotions that people are feeling when they come to attractions have changed over the year?
The expectations change, and the value, what do they feel about the value when they go to these places? So I’m really excited to dive into that.

Angie: My favorite topic, we can see what the complaint levels for restrooms are across different visitor attractions globally. Just in case you needed to know.
If you like the show, come and find us at dexibit.com or send us your questions at info@dexibit.com.

If your goal is to get more visitors through the door, engaging and spending more, leaving happy and loyally returning – check out Dexibit’s data analytics and AI software at dexibit.com. We work with visitor attractions, cultural and commercial, integrating with over a hundred industry source systems across visitor experience and venue operations, providing dashboards, reports, insights, forecasts, data management and a unique data concierge.

Until next time, this is Dexibit!

Angie Judge: Hello and welcome, my name is Angie Judge from Dexibit and welcome to the Data Diaries. I’m here today with David Hingley. David, good morning.

David Hingley: Morning. Good to be with you.

Angie Judge: Great to be with you! David has spent the last 12 years leading visitor services and operational excellence in the UK’s leading cultural institutions, and he’s sharing his passion with others up and coming in the industry. From a career in FMCG retailing, David has worked at the Historic Royal Palaces and then the Landmark Trust before going on to head Visitor Experience at Tate across both Tate Britain and Tate Modern since 2019. And he’s also a trustee for Painshill Park and is currently running a series of 10K runs to raise funds for mental health too, I understand. Looking for a bit of sponsorship there, David?

David Hingley: Yeah, always looking for sponsorship. I’ve done 10 runs so far this year and I’ve got two more to go.

Angie Judge: I would gladly be on the paying side rather than the running side. It’s definitely not my cup of tea.

David Hingley: I’m definitely banking on that with a lot of my supporters.

Angie Judge: David is going to share with us today, one of his great passions and how he’s sharing his work in the industry, helping visitor services and frontline teams of the UK’s cultural institutions to – what he calls, “Cross the Floor” – to swap and share in their experiences and gain new ones. So, David, I’m looking forward to hearing all about this. Perhaps you could start us off with a quick overview on what “Crossing the Floors” is all about.

David Hingley: Yeah, absolutely. It’s definitely a bit of a soapbox of mine. So people that know me and have worked with me know that I’ve been sort of banging on about this in different forms, for quite a while, but essentially it’s a really simple idea. It’s the idea that a lot of the teams that work really broadly in front of house, so visitor experience, my teams, but also areas like ticketing, security, et cetera, they don’t get the same opportunities that other areas of the organization do to just dip out maybe and grab a coffee with a colleague in another institution, or spend time in another museum or a cultural site as part of their work. Because their work is very much normally around being rooted in certain places at certain times so that the site can operate. So talking to the team, one of the things that they wanted to do was have wider experiences and we were thinking about how we could do that, and just one simple way that we came up with was to be able to go and spend some time with a similar or even slightly different institution that was kind of relatively close by, because we’re always thinking about the cost for the team member, for example, to do a different commute, but, you know, go and spend a day shadowing a shift, buddying up with a colleague and just see what it’s like. So, for example, Tate Modern sits facing St. Paul’s Cathedral, and they’re both big tourist sites, but they’re very different obviously, in terms of what they offer. So what “Crossing the Floors” does is it gives people an opportunity to think, especially those people who are just starting off their career and maybe working for Tate is their first job. They may well love it, but they may also be trying to work out what they want to do longer term as a career. This gives them a chance just to go and spend a day and just get a taste of what that might be like. Whether that’s for them, whether it’s not, but also a chance also to see how things are done differently in different places. Because I think you can become very kind of focused on your own institution. So it’s nice to kind of take a step back and see something different.

Angie Judge: And how do you get around this kind of constraint that you mentioned there of as a frontline person, these people would need to be onsite for it to operate. Is this something that they’re doing on work time? Is it out of work time? How do they manage, you know, that need to be present at their own institution?

David Hingley: Yeah, so we’ve worked really closely with partner organizations to sort of see how we can make this work and everybody’s gonna do it in the same way, because we thought that was really important. And it will be done on work time. Again, I think the culture sector can depend a lot on people getting experience through volunteering, and we thought it was important to be able to give people the chance to do something at their regular rate of pay. So they will work with a buddy. So it does mean that each site’s got to free just one person up for a day. We can run this scheme, we can have people who are interested put their names forward. We’ve been very clear that we kind of have to plan ahead to make sure our rotors work, et cetera. But then we can drop people in over a number of months into their kind of chosen site on days when we are better staffed and we know we can afford to do that. And the place where they’re going, whoever’s hosting them, knows that, you know, “Alright, they’re getting somebody who we’re not gonna leave them on their own, but we do know that these people have transferrable skills. They’re going to be great at talking to visitors at customer service. So they’ll bring that along with them.” So in a sense, you probably get kind of the equivalent of an extra half-person, they’re on your site for the day without leaving them, you know, unsupported. Because it’s really important that they’re with somebody and they’re looked after and that’s part of it. We’ve got six different organizations at the moment who are working on this and we’ve already got people that want to join us and expand. It’s easier to spread the load between us, whereas if we’re trying to do training kind of for our own teams, it’s really difficult to get more than a few people off the floor sometimes.

Angie Judge: Yeah. There is sort of a critical mass that you need to reach in order to do training across frontline teams, isn’t there?

David Hingley: Yeah, absolutely. So really one of the things we are looking at as well, is sharing the kind of training courses that we run because we recognize there’ll be a lot of similarities and I may only be able to get a couple of people off the floor, which would mean running a course for my team wouldn’t be cost effective, but if there are other teams that want to run a similar course and they can all get a couple of people off their floor together between us, then we can run the course.

Angie Judge: And I have to ask, in today’s tight labor market where it is quite difficult to attract staff, and I know so many cultural institutions are feeling that pinch at the moment and are short staffed. Does that become a little bit of a risk in terms of letting staff walk out the door and across the way to someone who I imagine isn’t quite a competitor, but equally another workplace that might entice others away?

David Hingley: Do you know what? I think it’s always a risk, but I think it’s that classic, there’s absolutely a risk that if you don’t do something to look after and develop your team, you’re going to end up with individuals who are frustrated, who want to get on, but aren’t seeing the opportunities and who are probably gonna look elsewhere anyway. So I think there are two bits to it. It is a tight labor market. We’re all pulling on, effectively very similar pools, but we’re talking about how we want to change that pool of people in the future and attract more diverse individuals, for example, in the culture sector. And I think each institution is not gonna be able to do that on its own. So by pulling together, you know, maybe I’m a firm believer sometimes in getting the right person in the right place. So there could be somebody who’s a little bit demotivated, maybe isn’t sure that my place of work is a place for them, but they go and experience somewhere else. They really find that that is where they want to be. And then I think you’ve gotta take a broader view that that is good for the sector. And you know, I’m a believer that our organizations are, although we would quite often say they’re large, they’re not large in the scheme of the world. I’ve worked for kind of major blue chip companies where we had tens of thousands of employees, lots more opportunities to develop. So I think what we can do by giving people the opportunity to see what else is out there is they have an opportunity to develop. There’s not necessarily always somewhere for them to go where they’re currently employed, but it may be they go away and come back and they’ve got some experience in a different role. So I think, yeah, I’m a firm believer in giving people that opportunity.

Angie Judge: Very well put. And I know I love hearing your passion that speaks to the way in which a visitor services or visitor experience career is a profession in its own right. I’m curious, at what moment in your own career sort of sparked this inspiration behind starting off this effort around “Crossing the Floors”?

David Hingley: Yeah, I think I’ve always been interested in that kind of, I think if you work with lots of people, you know, you always get interested in what makes people tick, be that the visitors and customers or be that your own team and how that interaction between individuals is the point where, let’s be honest, whatever your product, whatever area you work in, that’s kind of the moment when it happens. And that’s very, I think that’s very personal. So I think it’s really important. Whatever else goes into an experience or a project is that kind of interaction moment where it actually happens. That for me is the most important part. And so I came to the conclusion that whatever else people did in the background, when I worked in department stores, or now I work in more creative and cultural industries, that personal interaction can totally ruin everything else on the downside or it can totally make up for something that’s not quite working in the way that you’d hoped. So I think that is a real, it’s often overlooked and partly that’s because it does just happen because, you know, we are just human at the end of the day, and we try and get on with each other most of the time and we try and make things sort of work as well as they possibly can. On the one hand, that’s quite a simple thing because we do it all the time in everyday life. So we all think we can do it. But delivering that day in, day out for very different audiences that may be coming into the same place, that is a real skill. And I think you learn that over time. So I think for me, probably there was a point at which actually when I was working in department stores, when I decided that I actually really liked that part of the whole journey. And I have done roles where I’ve been further away from that kind of interaction, and I’ve just found I don’t get the same buzz out of it and I don’t enjoy it as much. And I also think the teams in that expert field of operations, visitor experience, more broadly, I think they’re people who what gives them a buzz, is usually seeing somebody go away who’s had their experience turned around if they were maybe not having a great time or who’ve had their experience really moved on to the next level. People write in, I always kind of joke a bit, but people write in, and this is the same wherever I’ve worked. And they don’t say the art was amazing at Tate Modern. I mean, they do, but they kind of expect that because it’s Tate. Or when they go to a royal palace, they expect the royal palaces to look amazing, to be stunning, to be full of history. That’s kind of a given, which is slightly unfair, but that’s the deal. But what they write in about is the member of staff they met that told them the little secret or the thing that they couldn’t read in the guidebook or the writing about the sandwiches in the toilets. But I think it’s really important that you leave a real impression on people and I think that can get so overlooked because it’s really hard to quantify actually. You can do mystery visit scores and you can, you know, there’s all kinds of things you can do. It’s quite hard to tap into just what it is people do because if you’re doing it right as well, it seems effortless and I think that’s really hard. It’s almost, the better a team is at it, the less it gets noticed.

Angie Judge: That’s so true.

David Hingley: Because we always react and again, team people that work in these teams, I think are naturally predisposed to kind of look at what went wrong and try and fix it for next time.

Angie Judge: And David, I wondered if there’s a moment that you’ve learned through “Crossing the Floors” or seen somebody else learn that sort of light bulb moment of those secret ingredients that go into that secret source that delivers that really special visitor experience.

David Hingley: It’s really interesting. I’ve seen it where we’ve taken, even just taken people in on work experience at different levels and they’ve quite often been really nervous about, you know, the first time you go and work, usually you end up wearing a uniform. If you are in a big visitor experience team, as soon as you put that uniform on or that name badge or whatever you do, the pressures on. Everybody assumes you know everything. And I think what I’ve seen quite a few times is where you say, “Well, we’ve partnered you up with this person today.” And it’s usually somebody who knows the institution clearly, someone who’s really enthusiastic about it. What we found is if you say to them, “While you are with that person, just kind of ask them about what their personal favorites are. You know, what little stories they’ve got.” I have seen quite a few people really blossom on the fact that what they’ve realized is, you don’t need to be an expert on everything. You can’t. But if there’s a few bits that you really know and you really love, and you really learn to kind of tell that story or share that in the way that you want, that can really make a difference. And I can think of people who are quite quiet, although, you know, great at meeting and greeting, but you know, quite quiet as an individual. You would say they were outgoing, but they, they pick up these bits from people that they’re buddying up with and you can see they think “I could do this because there’s something in this space where I’m working that I’m massively passionate about, and I know I’m not gonna have a problem talking to somebody about it for five, ten minutes if that’s what I need to do.” So I think that’s what you see people kind of take away from the experience.

Angie Judge: It’s a great leadership mission, isn’t it? To connect with your “why” and find your personal passion in there that helps you love your work.

David Hingley: Yeah, I think that’s it. And I think one thing that I’ve reflected on is, and that probably has made me even more passionate about the idea that this is a real career for people, is that you come across people who are so passionate about what they do. Whether you meet people, for example, who work at Tate, who are practicing artists as well. And this is just where everything connects for them. And that’s fantastic, but it’s, you know, it’s also great because it’s something that they want to share with people.

Angie Judge: And so, outside of that passion, what are some of the big skill gaps that we as an industry need to address?

David Hingley: One of the things I used to kind of give regular talks to museum studies groups, which I always loved doing. I think a lot of people in the audience, and this is not to say that you shouldn’t want to become a curator, but they’ve kind of, the job they’ve heard of is being a curator in a museum. So that’s what they want to do. I think this happens in lots of organizations, actually. There are certain jobs that you just think, “Right, that’s the job I want. Cause that’s the one I’ve heard of.” So actually one of the gaps is in people being able to understand what the structures are that are behind working in, for example, a museum or heritage site. Such as the ones I work in at the moment. You can work in marketing, you can work in maintenance. There’s a whole structure there and I think one of the gaps is that we just don’t make people aware that we do need those skills. So it’s kind of a catch-22. I think what people naturally want to do is to specialize in an area and so actually one of the skills gaps is in, I would say if you work in Visitor Experience because you’re the end result of everything else in the organization. You are the kind of point of delivery. You do get to see everything. So you get to work with every single team. And that in itself is a skill to be able to balance that and to be able to put across your experience in dealing with customers to say, “I know this looks great on paper, but in the nicest possible way. I don’t think it’s gonna work when it comes into contact with people.” And I think another gap is having people who don’t necessarily have a massive understanding about everything, but a great understanding of specific things. Sometimes you’ve just got teams on the front line who know the visitors who operate in those spaces every day, and it can be something as simple as everybody always turns left when they come through that door. There’s not necessarily any deep logic as to why that is, but that’s just what the humans have been doing here for ages. So don’t build an exhibition where you need everyone to turn right because they’re gonna get confused. Sometimes there’s less understanding of the importance of really having, not just having the data, because I think we’re quite good at having data, but analyzing it and seeing how you can get the best possible use out of it. So I’m thinking about things like, how many people go through an exhibition in a day, and really breaking that down. I think people don’t tend to work on the detail of like, how many people did you get through that hour? How many people did you get through the next? How does it vary? How can you maximize and make sure the experience is as good as possible while still having the ticket sales that you want? And I think that’s an area that when I moved from retail into heritage and culture, I felt that the sector has been behind on at times. It almost feels like it’s not somewhere where people wanna get too scientific about it because it might ruin the magic, but I think it’s quite the reverse.

Angie Judge: That’s so true. I’m so glad you brought up data and insight as part of that skill gap, because I think what we see in our work is that the visitor experience and visitor services teams in a venue or a museum where data is incredibly successful, they are the number one consumers of data. They look at forecasts to do their rostering. They look at visitor sentiment to see how happy their visitors are. They look at exhibition performance against goals. Again, they look at revenue, average revenue per visit, and how they can improve it and get visitor services into that state of play. There is quite a big leap to make from how we’ve operated in the past. Right?

David Hingley: Yeah, definitely. I think I’ve often been surprised by the fact that data doesn’t actually get to the teams on the ground sometimes. It’s almost like it’s analyzed, understandably, it’s analyzed financially and all that, but it’s not necessarily looked at by the visitor facing teams. And I think there are always gonna be some members of the team, and that’s fine, who aren’t into all of that detail. You don’t need every single person to know the minutiae of it. But certainly, at a management level, I think it makes such a huge difference to be able to stand back. I mean, we’ve all had it happen when we work operationally, where you think at the end of the day, “Gosh, that was a busy day. You know, we must, we must have had a really large number of people come through.” And then you look back at the counters and, you know, oh, it wasn’t as busy as I thought. It just happened to be one of those days where we dealt with a number of issues. So that’s really helpful, I think. But the reverse is also true, sometimes you think, “Gosh, that didn’t feel like it was a busy day,” but actually what it means is you’ve had huge numbers of people through, you’ve hit your targets, but you’ve managed to do it in a really good way. And to be able to go back and look at that and say, “Right, how do we repeat that experience so that having X thousand people through the doors over a weekend so it doesn’t feel painful? I think that’s really important.

Angie Judge: Yeah, and you hit on such an important point there that often we haven’t democratized that data to those frontline staff. That it is sitting in the finance department, or the marketing team are the ones with all the tools, and yet our visitor services teams are the ones who have the most context to add to that data. Of all of those things that went on, on that really big weekend that made it feel heavy, and they’re also the people that can provide the most actionable moments to that data as well when we see those opportunities for improvements of, “How can we repeat that beautifully scalable, seamless weekend and do more of them in the future?”

David Hingley: I do think that one of the things that came out of the pandemic, and I think it’s still really important, is when we had to be really careful in terms of how many people were in a building, how we operated the space. We had to keep so much space, I mean there were legal reasons as well. While we needed to do that, it really focused the mind on what we were able to do. And what we were able to do was get really live information from surveys that say “How safe did visitors feel?” Cause that was the number one thing above everything else. How safe did people feel so that they would continue to visit and come back? And because we were getting that almost as a live feed sort of at least kind of once a week download, we could make changes and we could see how those changes were affecting the experience in an exhibition, for example. And we could do that kind of week on week. I don’t know if you could do it any more than that. I mean, you could possibly do it more than that, but sort of week on week was really manageable actually. And I think one of the things that I have taken away is, another one of these areas where I think it’s really important to work as consistently across organizations is because visitors were going to your competitors, if you want to call them competitors, or going to, you know, I think people will always go to the National Gallery and Tate because we’ve got different art, different exhibitions, but, you know, people having both those experiences. Safety and fun. So to be able to make sure that, to a degree it’s aligned in terms of people won’t go to the National Gallery and think, “Gosh, it’s brilliant they did that there, and yet Tate does none of it.” I mean, if stuff’s working for visitors, you kind of wanna grow the whole experience rather than just focus on an individual area, an individual site. Because it just doesn’t work because they always come back to you and say what they saw elsewhere that they loved.

Angie Judge: And speaking of these pandemic trends, we are sort of in this very weird time of hyperinflation and these tight labor markets that we were talking about before. Are we in a spot right now where the industry is understaffed on the frontline?

David Hingley: I think it’s a challenge. I’ve heard different things. We’re fortunate that we’ve recently been recruiting and we’ve had a really good response. I’d like to think some of that’s because people can see what it is we’re offering and that we are absolutely saying there are opportunities to work as an apprentice, for example, and kind of move through the visitor experience. So kind of a career ladder if you like, but also we’re being quite open and saying “If you’re looking for an experience, come to Tate, work with us in visitor experience and we’ll hopefully help you to think beyond Tate if that’s where you need to go.” So I hope that’s insulating us if you’d like a little bit from that. But it’s definitely tight and there are other opportunities. So I think it’s gonna be increasingly, and I know this has been a trend over quite a period, but I think it’s kind of accelerated why it’s important that this is a career. We live in a gig economy world, and you can choose to work on contracts where you might come and support different organizations for different events, et cetera. And that really suits some people. But I think it’s being able to say that there’s another option, and the other option is kind of building a career in the sector. You can’t always necessarily compete on the salary because some of these gig economy roles, you know, somebody’s desperate and they’ve got an event to run so they can offer a good hourly rate, and it’s up to people whether they want to take that, understandably, they may need to, but I think to be able to say, “Look, there’s different ways of doing this” and just kind of be really honest about what it is you can offer, I think that is hopefully helping us to insulate a little bit against that, but it, it’s definitely a tough market at the moment.

Angie Judge: What are you looking for in the staff that you’re hiring that are new to this role?

David Hingley: I’m looking for people who are passionate about people. Actually, first and foremost, I think it’s great if they’re passionate about, in Tate’s case art, but equally sometimes some of the people who maybe come from a retail background, et cetera, who are great with people. I mean, our whole selection processes have moved to looking at personal interactions, group exercises, those kind of things to see how people are at talking to and engaging with other people. Because quite often people who don’t have that arts background actually suddenly come across an artist that they’ve genuinely never heard of who might be at some upcoming exhibition, and they become so interested and excited because it’s completely new to them that they can carry that passion through as well. So people. Love interacting with people. It’s people who I think understand the variety of what you’re gonna deal with in a front-of-house role that, you know, if you’re open to it all, you genuinely will get every type of person in. You need to be able to think about what that will be like and will feel like, and we support people obviously, but you know, sometimes you can have difficult conversations. It’s not always easy doing the kind of roles that we’re talking about. And then I’m absolutely happy for people to come in and work with us and get early career understandings of what the culture sector is and then they may move on to work in a different area. think it’s always good that people have had front-of-house experience. But I’m also looking for people who do want to build a career in front-of-house, who do want to be the managers of the future and can see the opportunity to kind of shape what the experience is by moving up in that.

Angie Judge: And where can these careers take people in front-of-house for visitor experience and cultural institutions?

David Hingley: Yeah, I’ve seen people that we’ve placed in different roles within the same institution. I think what tends to happen is people who are really passionate about it use this as a springboard. We’ve had people go and join our learning team, so move from visitor experience to kind of more formal learning and engagement. So that’s great. Looking after family program development, that kind of thing. We’ve had people who’ve moved into curatorial roles, particularly in areas like if you think about kind of program production and delivery. So looking kind of more broadly beyond the day-to-day delivery. So they’ve already got those skills. They take them, they take that on. We’ve had people join other teams simply because they’re just really good at customer interaction. We have visitor communications teams who look after a lot of the emails, calls, et cetera. So members of my teams have moved into that. And then I’ve had people who’ve kind of taken first management roles, if you like. When I went to historic royal palaces at Hampton Court, whenever anybody left, we used to try and encourage people to think of it as us gaining another museum. So we had people who’d kind of start with us, build up their experience and then go and run. I think we had somebody who went to Oxford Castle for example, someone who went to the Ashmolean, which is another museum, and they were able to take what they’d learnt and then kind of take the next step up and then bring us back to “Crossing the Floors”. Then that’s increased the network and we’ve got somebody else that we can contact and say, “Can we work together in the future?”

Angie Judge: And what would your advice be if somebody wanted to attempt, replicating your initiative in another country or in another city? What would you suggest to them in terms of how do you go about getting something like this off the ground?

David Hingley: I think I absolutely mercilessly pitched to people who I thought would be interested in my personal network. There was a bit of that. I think it was very much around, I think people were keen to do it, but I think we’re all, we’ve talked about it. It’s tough at the moment in the labor market and we’ve got a lot going on, so you can become quite focused on your own problems and your own institution. So actually I think the group we’ve set up, we’re also a bit of a self-help group at times where it’s like, we have worked out together how this is gonna work, and I think that’s been important. Without a huge amount of investment, et cetera. But you know, what I’ve been able to say is that I’m one of the bigger teams involved, so we can take on kind of quite a lot of the admin and such to support other smaller organizations. And one of our organization values is to be kind, though I think in a sense it’s like what are your organizational values? Do they align with the other organizations you’re gonna work with? Because then, you know, you’ve got probably a very similar start point. And the other element is just sorting out the admin because you can imagine the admin people thinking, “Are they gonna go and work at a different site? What’s the insurance? How are you gonna cover that? Different organizations can have different kinds of security clearance levels.” So getting all that sorted in the background has been important.

Angie Judge: I can’t even begin to imagine what that looks like.

David Hingley: There’s quite a lot of spreadsheets, you know. That’s good. Once we’ve got it off the ground, I’m sure as well it’ll get easier.

Angie Judge: Well, thank you very much for taking a few minutes out of your day and all of that paperwork to share your “Crossing the Floors” initiative with us. It’s incredibly exciting to hear in this post covid world that the way in which cultural institutions came together to collaborate and to work together as an industry as continuing on in lots of different ways, I’m really excited about that.

David Hingley: Yeah, I’m really looking forward to seeing how it develops and I’m kind of excited. We’ve got other organizations who are interested, so hopefully we can just build on that and as you say, keep working together post Covid.

Angie Judge: Hello and welcome to the Data Diaries, I’m your host Angie Judge of Dexibit. Today I am here with Arthur G Affleck III, Executive Director of the Association of Children’s Museums. Welcome Arthur.

Arthur Affleck: Thank you for having me.

Angie Judge: Now the children’s museum field is one of the fastest growing cultural in industries in the world. And ACM is its international nonprofit for representation and advocacy. It has over 480 organizations and members across 16 countries and 50 states. And Arthur is very well known in the industry for his achievements in education administration, institutional advancement and nonprofit governance, centering diversity, equity, accessibility, and inclusion. Before ACM, he served as EVP at the American Alliance of Museums. And he currently serves on several nonprofit boards, including for the International Council of Museums who just had their annual meeting in Prague. Plus Bottom Line, New York, Crystal Bridges, and Playful Learning Landscapes. And he’s also an accomplished author too. That’s quite the resume Arthur!

Arthur Affleck: Well, thank you.

Angie Judge: Thank you for taking the time out of that very busy lineup to join us here. Today is a very special topic that I’m really looking forward to. Because as of a few months back, I joined the parents’ club and it’s really got me thinking about my own parenting style and how we want to approach education. We’re going to talk about the ‘power of play’ in children’s learning and experiences and cultural institutions and beyond, and how the work of the Association of Children’s Museums is not just representing the interests of their museums, but changing the way children learn, which is a really big departure from the ‘desks set in rows’ that we all grew up with and an incredibly powerful mission. And when we were exchanging ideas ahead of today, Arthur shared with me a great quote by the late great Fred Rogers. That “Play is the real work of childhood”. And he also went on to specifically say, this is Rogers speaking, “That children’s museums offer play experiences that other settings are not able to give them.” That’s quite the ultimate endorsement for your work I imagine!

Arthur Affleck: Yes. Yes. And I just should say that some years ago in 1996, actually ACM gave Fred Rogers, our ‘Friend of Kids’ award, and he gave the talk and the keynote address and shared some of those thoughts, but we give that award out every year. So we were thrilled that Mr. Rogers would come and, and obviously knew he shares our love of children and love of play.

Angie Judge: You must get this a lot, but perhaps you can set us off with what a children’s museum actually is. And, how does it differ from other museums?

Arthur Affleck: So first we like to talk about the four dimensions of children’s museums. First as local destinations. Second as educational laboratories. Third as community resources and fourth as advocates for children. Now a more traditional definition I could give is a place where people come together, children and families, to understand the world and their place in it. Some museums do that through art, others, through natural science specimens. And children’s museums do it through immersive play based hands on experiences. So that is how we differ from a museum that focuses more on collections.

Angie Judge: And what led you to your role as ED at ACM?

Arthur Affleck: So very interesting. I have always, for most of my career, worked in education in higher education. As a matter of fact, I originally wanted to be a school teacher, a science teacher. I went to college for biology pre-med, but wound up going to graduate school for a degree in higher education leadership, and then to law school. And after a few years, working at a law firm decided to get back into education where I felt more fulfilled. And every university where I worked the last 10, 15 years had a museum. And I loved those museums. And so the opportunity came about six years ago to work at the American Alliance of Museums. And I jumped at the opportunity and it was a great experience there for six years. My last role, as you mentioned, was Executive Vice President. And then for the last six months, I had been the Executive Director of the wonderful Association of Children’s Museums.

Angie Judge: And what are some of the sort of current opportunities or challenges, the work that you’re facing right now?

Arthur Affleck: We are emerging from the pandemic. So as an organization working to, I’m look at my team and building my team. You may recall the book ‘Good to Great’, which said, those who build great organizations, make sure they have the right people on the bus and in the right seats. So I’m looking at my team and I have a very strong team, but we’re looking at roles and responsibilities. And so we’ll be making some changes there and then we’re going to grow the team. We’re hiring additional people because the demand for our services is greater than ever. But some of the challenges that, that we also have – technology, we’re upgrading our technology. We’ll be bringing on a new database for us, but when it comes to the children’s museums, some of the challenges they’re having. We spent a lot of time doing virtual work and now that we are focused on in person work and some of them are not fully back in terms of staffing, 100%, they’re struggling to say, how do we fully give the in person experience yet not lose all of the great work we did in the virtual space? So that’s one challenge. Staffing is a challenge – hiring and retaining staff – because we are not able to pay right as high as some other entities. So that’s a challenge. We’re facing funding as a challenge. We have to work harder for revenue and support because when you have a pandemic and people have medical challenges and people are unhoused and people have food insecurity, a lot of charity kind of shifted a little bit for those resources, but we make the case that man or woman does not live by bread alone, that we must feed our souls and our children and adults need access to culture and the arts to behold. And in fact, if you think about the mental health crisis, we know that we are even more important as children’s museums that is to the children and families than ever before, because while we don’t solve those problems, we ameliorate those symptoms because when children play they’re joyful and in the process they’re learning and families are engaging and we can see that they are having a very positive emotional, mental and physical experience in our museums. So we are vital and we must fight for those resources, just like every other organization. We’re thrilled to be here. The challenges are not as many as the opportunities. We have many great opportunities that I’m very excited about.

Angie Judge: And what is the science and the data behind this say what, what supports the value proposition of play and play based learning?

Arthur Affleck: There is a lot of data and information around play and play based learning. I will start with an article since your podcast is all about data, right? So I’m going to refer to an article called ‘A New Path to Education Reform, Playful Learning Promotes 21st Century Skills in Schools.’ And this 2020 paper has 150 references, to back it up and support it. And this paper was written by one of my colleagues and friends, Dr. Kathy Hirsh-Pasek and her colleague, but essentially they start out by talking about the American education system, just not preparing all children to thrive. So that’s a big challenge right there. The data shows that in the science of learning, narrow content focused education, the didactic method, is insufficient, works for some, but is insufficient. And so we’re calling for scalable evidence based education that puts student engagement, educate expertise, and equity at the center. And so we believe that play and play-based learning and the data shows it helps students and teachers make learning more active, engaging, meaningful, socially interactive, iterative, and even joyful. And when it’s joyful for the students and for the teachers, not only do the students learn, but the teachers are better retained. So that’s one, and I’ll give you another reference for play-based learning and, and another endorsement. And that is the American Academy of Pediatrics. They put out an article, many articles, but there’s one that, that I referenced and it’s called ‘The Power of Play, a Pediatric Role in Enhancing Development of Young Children.’ And so that article talks about the fact that children need to develop a variety of skill sets to optimize their development and to manage toxic stress. Basically research demonstrates that development developmentally appropriate play with parents and peers is a singular opportunity to promote social, emotional, cognitive language self-regulation skills, et cetera. So lots of references from the medical field, from academics, from teachers that play in play based learning is the way and from none other than Fred Rogers.

Angie Judge: It’s incredible. Especially following a couple of years where our kids have been learning in front of screens, really. And it’s so different to being able to sit and play with each other. And you mentioned equity in there. How does this whole approach address some of those inequities that we face in early childhood education?

Arthur Affleck: We believe that learning through play is accessible to every child, to all students, to all families. It’s not based on your income level, it’s not based on your zip code. It is based on the ability of the institution of the school, of the museum to implement this methodology. And, and we find that play based learning can be made to be culturally sensitive and culturally specific, because play is viewed differently in different parts of the country, different parts of the world. They view play a little differently, but play-based learning can be moulded and modified to be culturally specific and therefore help students to be engaged. I’ll give you an example of that. If you are from, maybe your cultural background is from Latin America. Well, there are things in that culture that animates children and families. So one way to get to play and feel comfortable is to play some games that they would be familiar with from that culture to reference, you know, some of the characters from that culture that would be of interest. And you can do that with every culture, whether it’s African American or whether it’s, you know, Asian or what have you. And so when we work with schools and we are talking about our academic partners and museum educators, we always look at how we can make sure that we are creating culturally appropriate kinds of opportunities for children to engage and to play. And then the other part of play, you know, play comes on a spectrum, you know, there’s free play and there’s an argument for free play because we believe play is learning full stop. When students are playing, they’re learning, there’s free play, but free play doesn’t have a learning. Children are just doing their thing and having a great time. But we believe guided play is what we use in museums. More often where the child does indeed have agency and is actively engaged and involved, but you have an educator or a museum staff member kind of guiding the child toward a learning objective. So it’s still fun. It’s still engaging, but there’s learning going on. And at the other end of spectrum of play and learning is direct. Instruction, you know, where students are sitting down, they’re being told what to do and how to play. And that we think is not the best way to go about it because we need children to have agency. We need them to have the feeling that they’re making decisions about how they want to play and just, and, and they can be guided then in ways that make play even more important and even more meaningful. So that. That’s uh, what I would say about why we, we know that more equity can be achieved if playful learning is utilized. And we can see that in, you know, some of the data as well.

Angie Judge: That’s so interesting. When you talk about sort of the cultural elements of play, and one of the things where I come from in Aotearoa or New Zealand, there is a, a respect for food, which means that it can be  somewhat offensive to have children playing with food, which is quite common in the Western world. You know, you think about things like play-doh, or making macaroni sculptures or playing with rice. But here that’s very different. So it’s really good to hear that be incorporated as part of this view on play-based learning. And Arthur, I understand your team are working on a new strategic plan? Can you share any of that in terms of your preliminary findings or some of the priorities that are coming out of that work?

Arthur Affleck: Yes. So we are, we should have this plan done by the end of the year. It’s been fascinating to move around the country and to receive input from our members, from education leaders, from our board members and others. Right now we’re emerging, we have four major priorities that are on the draft plan. And the first of those priorities is that we will continue to support the children’s museum community as, as a membership organization. That’s critical through convening and resources and connecting and research, et cetera, but a new plank that was not in the last plan is that we will have a separate priority focused on children and families providing indirect and services through our members, but also direct advocacy and work from the association. And I should say, Angie, this second plank came out of the awful experience that we all learned about and with the Uvalde shooting, when all of those children were lost in that school, meant some of our board members came together to say, it’s not enough that we champion our mission statement. Our current mission statement says we champion children’s museums worldwide. It’s not enough that we champion children’s museums. We have to champion children and families, and we have to fight for them to be safe wherever they are. So for example, our current mission statement, you know, says we champion children, children’s museums worldwide, the emerging mission statement, the draft mission statement says, “ACM champions children’s museums and empowers children to play, learn and thrive safely in these vital shared spaces worldwide”. So that’s a shift that we are going to do more to advocate, not just for children to play and learn, but also to thrive safely in these vital spaces in museums or schools. Which means that we will, I’ve had conversations with the boys and girls clubs of America. I have conversations with other organizations that we won’t go with alone, but we will join with other organizations advocating on behalf of children to be safe funding for schools. We’re gonna fight with others for universal pre-K, all of those things that we know make a big difference. And I know at some point you’ll let me share some data. You know, school readiness and, and why it’s so important that we, we have this early childhood education, but let me finish responding to your question. The two other planks in our strategic plan. So one was the children, museum, community, two children and families. Advocacy policy and research and advocacy is so critical. We work with federal government educating, sharing information, making sure they continue to financially support the museum community. We have museums advocacy day, every year, working with AAM and other associations. And we have been successful in maintaining funding for our museums. And the last one is strengthening the organization, that we will work to strengthen ACM as an organization. So we can be more impactful to our members, provide more direct services, children and families generate more revenue to offset the work that, that we are doing and to hire and retain more staff. So all of that is in our new plan, but the newest plan is, and I’m excited about this work to think about how we can do more direct work with children and families.

Angie Judge: This is such a radical leap and it’s such an amazing vision to have. And you mentioned the origins of that an absolutely horrific situation, but it does go on to highlight the need for this safety of our kids. But, and not only that, but the children that grow up to experience problems through their early years and the impacts to society that that sort of creates, these shootings that have taken place. The people who are the offenders in that situation are, are young people themselves. Aren’t they, in, in many cases, Arthur, you mentioned some of the, the data that are coming out of some of these elements, the statistics on how kids are ready for a kindergarten and the relationship of how we set up our kids to enter the academic system and then the socioeconomic trajectory that, that sets them on. If they essentially learn to hate learning and then never catch up, what does the impact of that problem look like in data?

Arthur Affleck: A child’s learning, and it’s not every parent just doesn’t know this, but a child’s learning from birth to five is critical. It determines their kindergarten starting point. Students who enter kindergarten behind have a monumental undertaking to catch up with their classmates. And so the data show that one in four kindergarteners are not ready to learn. Some of this comes out of the Pritzker Family Foundation report: low income black and brown children are almost two in four, almost 50%, approaching, kindergarten, not quite ready to learn. For students who enter kindergarten one or two or three years behind, it is very difficult to make sufficient progress, to move up even one level without a massive amount of intervention. So, so, you know, we are hopeful. We believe all children can and will improve. Right. But for those who enter kindergarten, the data shows 75% will never catch up to their classmates. This means that each child’s kindergarten starting point matters. And this is according to the Children’s Reading Foundation data: that we have got to get more children ready for kindergarten. So children’s museums play a vital role in facilitating play and many school readiness programs exist to address this pressing challenge. And so we plan to do more in that regard. I remember being in the Please Touch Museum in Philadelphia and seeing that very wonderful school readiness program that just gets these kids ready so that they have socio-emotional skills. They have executive function skills, self-regulation skills. So they show up to school with literacy, numeracy, self control to the extent that they can indeed learn. And the point you made earlier that breaks my heart is that we know that if children are not prepared for school and they get to school, and spend years behind, school becomes painful because every day you are found out to be unprepared. You can’t answer the questions you can’t keep up. And the minute they get old enough to be able to drop out, we see millions of kids dropping out of school every year and they become, unfortunately, those young people that often get into difficulty and get into trouble. And the data show that a high percentage, 75%, if not more, of convicted felons in prison are people who dropped out of school didn’t have a good school experience. So we know that the dire consequences to society for not paying more attention to early learning. And our goal is to advocate for more, to do more within our institutions and to partner with others who also understand this.

Angie Judge: And that’s not just about crime, is it? Because in the last few years we’ve seen mental health for both adults and kids become more front of mind  for our society and indeed more pressing, how does play help with that?

Arthur Affleck: And you are exactly right. The two crises, one is mental health crisis. The other is the early learning crisis, but they’re related, right? They’re definitely related. So, and I think it was the in readings from the American Pediatric Association talking about the fact that play is good for the physical, the mental, the social, and the academic growth and development of children. And there are studies that show how young people who are allowed to play as the American Pediatric Association said, it helps the toxic stress that they experience in their lives, that we can’t avoid some stress. But what the data show is that if children are allowed to be in those environments, where they can release that stress by playing freely and even through guided play with facilitators, but also playing with parents, the other benefit of play that supports mental health for parents and that playing museums and our museums is intergenerational. I was in with the Louisiana Children’s team a few weeks ago. And saw a grandfather with his daughter with his granddaughter in this play space, watching the granddaughter, you know, a toddler playing and he reported, he just volunteered to me, “We come here twice a week. She loves it and she’s learning so much and having so much fun.” So all of that, he felt great, he felt pride. The mother felt good and the child was having a great time. So, you know, we need to do more of this and provide more of this feeling. And again, it doesn’t solve the problem if you will, of mental health. But we also are beginning to work with our members to have trauma informed programming so that while we can’t solve the challenges when we, but we need to be able to identify trauma in families and in children and be able to help parents and families to services that can help them. And then also to train our staffs and we’re working to do that. So that again, you know, we, we have programming to say, first of all, it’s okay to be a little anxious. It’s okay to be concerned when things are happening in society, that nothing is wrong with that, but here’s how we process trauma. And certainly coming out of eval, more museums have been in programs, bringing in experts, bringing in social scientists, bringing in psychologists, bringing in others into the museum to talk about how we process trauma and all of that. And all of that helps with some of the mental health challenges that we’re seeing among children and families. And sadly, that is not going to go away tomorrow. They will be more. Tragedy, sadly in America, and in the world. So we just have to help children and families become more resilient. And that’s the goal of ours.

Angie Judge: And what are some of the other ways that the children’s museums are engaging with parents and other caregivers?

Arthur Affleck: So one of the exciting programs that I love is, a number of our museums have these, programs called ‘The First 1,000 Days’. And these programs, we understand that parents really are the first teachers of children. And if we can help parents understand how they can facilitate play in their home, how they can facilitate brain development in their children, the children will be so much more successful. So in collaboration with researchers and scientists and health professionals, artists, and educators, some of our museums have designed a support system to help parents navigate the first three years of this parenting journey. And so they come into the museum for programming and then they’re given tools and resources to take. So they can do some things at home. So that’s exciting evidence based collaborative with community resources. And that’s one of those programs that we want to expand to throughout the country to make sure that we are doing all we can because if we don’t start early with these children’s first 1,000 days, first three years, and then the first five years, you know, we give children a chance if we do that well.  So that’s a program that I think is, is exceptional, that, that we will do more.

Angie Judge: It all sounds like it makes a lot of clear sense, but I know it’s, it’s always hard to get everyone to recognize the value of change like this, particularly when it is quite dramatic from the traditional ways that generations have learned before that, is this an obvious way that the world is heading or do you have to really work to convince parents, teachers, government officials that we need to do things differently?

Arthur Affleck: I think it’s getting easier. It’s becoming more acceptable  for play to be accepted. And one of the things that helps I think is that we have not only children’s museums, not only academics, not only the American Pediatric Association saying this. But their corporations and foundations, like Lego that truly believe in the power of play and that promote play and that support with their resources and their programming play and play strategies. For example, as you know, I visited the Famous Lego House recently. And one of the Lego foundation’s aim is to redefine play and to reimagine learning. And they’re working toward, as in their words, the future where learning through play empowers children to be creative, engaged life, long learners. So we have allies, an increasing numbers of allies, and we will partner with Lego. We will partner with academics, we’ll partner with all these other organizations that want to do this. And superintendents, I’ve met with superintendents because helping them to convince parents and other teachers that this is, this is important. And if time permits, I’d love to chat about the New Hampshire program that I think is going to, to make a, make a difference. But I think it’s getting better. People are recognizing the importance of play and especially coming out of the pandemic where children were pent up in their homes, parents and others are realizing, kids have got to get out, they’ve got to play. They can’t be, you know, kept cooped up on these screens or in, in homes all day.

Angie Judge: Tell us about New Hampshire what’s happening up there?

Arthur Affleck: So one of the great things that happened in New Hampshire, a parent who believed in play and the value of it wound up running for office and became a legislator. And then she introduced legislation to say, we ought to have play and play based learning for pre-K and kindergartens in New Hampshire and lo and behold, it was passed. So it is now a law in the state of New Hampshire. But to implement play based learning in the pre-K in kindergarten classes, they decided to bring in the Children’s Museum of New Hampshire. They also brought in professors from the university of New Hampshire and one of my colleagues, Dr. Kathy Hirsh-Pasek and Dr. Kimberly Nesbitt from the University of New Hampshire, Kathy’s from Temple University and they put together a program to train coaches who would then go into the classroom and train teachers and work with teachers in the classroom on how to implement a play based approach to their curriculum. They’re not trying to change their curriculum, just implementing play based techniques. And I went up to New Hampshire. I met with the educators, I met with the children’s museum and that I went to some of these schools, sat on the floor with these kids and saw the joy in them And it works. It works. And so we are going keep looking at the data from New Hampshire. I may have mentioned, I went to California, met with the superintendent of Los Angeles unified school district the great  Alberto Carlo, and he’s doing great work there. He said, he’s interested in doing more round play and play based learning. And there are many others. And so we believe that this New Hampshire model will be carried forward. I was in Washington. And met with legislators there and they said they willing to take a look at what more can be done there. We actually have an event coming up, another event in Washington State and Seattle. So we think it’s gaining momentum and we’ll see other models like New Hampshire and each state might do it a little differently. And that’s okay because it has to be state specific, culturally specific, but the idea is to bring more play and for learning techniques into schools and into communities.

Angie Judge: And in doing that work, what is the role of the museum in changing how children learn and, and has this sort of shifted as a result of the pandemic, has, has the last couple of years changed that role?

Arthur Affleck: So, I don’t know that the last couple years has changed the role except that what it has done is that it has made the role that much more important and that much more relevant and clear. Let me give you one story during the pandemic. One of the things that many of our museums did was when children were cooped up in their homes, couldn’t go to schools. Couldn’t come into the museums, is that they created kits. That would help children learn. And with the support of their families. One story was the Children’s Museum in Phoenix, Arizona. They created over 4,000 thinker player, creator boxes for an entire school district’s kindergarters because those families and children were really struggling on with online work. As a result, the district saw that when the kids got their boxes, the dropout rate among families slowed dramatically. Also one of the parents told the district that the materials in the box were the first time the child ever had their own book, scissors and crayons, the first time. So that’s just one example. Hundreds of museums did stuff like that during the pandemic. And so coming out of the pandemic, we know that and then some became vaccination centers. As you may recall, some became places where you can just get wifi, whatever, that the community needed. Some were food distribution centers. Our museums stepped up, but learning and education was a central way that our museums help families and children. And we’ll continue to do that on going.

Angie Judge: And speaking of that wider museum community, I know for our listeners, they might be from cultural institutions that they’re hosting school groups through their venues, or even from commercial attractions who are appealing to kids, they’ll be wanting to implement some of these ideas around play based learning too. How are you going about sharing the work of your team for others?

Arthur Affleck: So we share in a variety of ways. Number one, we certainly have an annual conference, a really big show and tell, and it’s not just open to children’s museum professionals. We have lots of other folk who come to the conference. In addition, our website provides a lot of information in the form of articles and blog posts and this to other materials. We have a newsletter called hand to hand that newsletter has lots of information. As a matter of fact, the story I told about the museum, in Arizona came out of that hand to hand one of our hand, hand publications. And then for members, we have something called group site where members post question, share challenges, uh, and successes, cetera. And if people want specific information, most of our children’s museums get requests and work with, for example, other community organizations and certainly schools to bring them into the children’s museum to say, this is how we do what we do, and we’re happy to share. So if anyone is in a community with a children’s museum, that children’s museum will welcome that organization in to dialogue about what they can do together and to share inspiration.

Angie Judge: Very cool. And I know some of your work is actually outside of what we traditionally think of as a venue, if you like, or a cultural institution, because you work with cities and public spaces too, through landscapes in some of your work. What does that look like in those other spaces, in terms of learning with play?

Arthur Affleck: So playful learning exists, not only in the classroom, but outside the classroom in what we call these informal learning spaces, museums, a one informal space, but I serve on the board of an organization called Playful Learning Landscapes. And this is an initiative that uniquely blends the science of learning place, making and community cohesion, right? Transforming public and shared spaces into fun and enriched learning hubs for the further development of children, families, and, and communities. And the beautiful thing about the way that works is that these spaces are co-created. So if we agree in a community that a bus stop or basketball court, or a park or playground could be transformed, we work together. We have some ideas. We ask the community, what do you think? What do you want? Parents, children, others, so that they own that space. And it’s different in every city and there’s some international locations. And so this is a young organization, but has already had some successes. And ultimately we believe that certainly play is important for children, and young children, but play is important for all of us, play everywhere. Play throughout our lives, play for adults. There’s data to show that those folk who are playful and who play and who do puzzles and do other things live longer and don’t have as many mental challenges as, as others. So play is good everywhere for all of us.

Angie Judge: Oh, that’s good, Arthur, because I bought my son some baby puzzles the other day. I bought them home and immediately did them, myself, so it’s gonna pay off! And so you just returned from a tour of Europe, I know with ICOM in Prague. And you mentioned Lego there in Denmark, too. What were some of the things you could leave us with that have inspired you recently?

Arthur Affleck: Oh, just first of all, the international conference was great. It was inspiring to, you know, be first of all, Prague was a beautiful city, but to just have presentations on topics like climate change, leadership, diversity governance, resilience from colleagues who are from Kenya or Paris or Australia or California, Brussels, DC. So I met so many colleagues from all around the world, so that was tremendous. That was great to see that we have so much in common with these common goals and objectives. And then I went to London and the great joy there was visiting the wonderful museums in London and meeting with colleagues from cultural institutions and talking about ways that we can collaborate and partner. And so we will be doing more work with them. And then the National Children’s Museum Eureka, talk about inspiration. When I visited, it was a Saturday, the museum was full of children and families having the time of their lives. And one comment from that museum, in the museum, there is a wall of pictures and quotes from their ambassadors, remembering their days in the museum. And one woman who her name is Hannah. She’s a five time para Olympic champion, and she said that Eureka is unique. “Children are just free to go out and explore”, and she wrote, “you’re having fun, great fun, but you’re also learning.” And then many quotes like that from adults now who remember their days. And as I said, my final destination was in Denmark at the Lego house in Denmark and my host there was a wonderful gentleman. Brilliant kind, joyful, gentle. And showed me so many things. Lego’s been doing this for 90 years, and I mentioned Legos on this mission to promote, play and play based learning. So we are there. But one quote I share that inspired me as well from the Lego Museum. And you’ll find these words around the Lego House as well. “Only the best is good enough”. It means we will always strive to do better year after year because the children of this world. How’s that for inspiration!

Angie Judge: What a beautiful note to end on. Thank you so much, Arthur, for sharing all of those incredible worldviews on how learning is changing in different cultures in different places and what we are doing to, uh, further that in the museum field. It’s very, very inspirational.

Arthur Affleck: Can I share one last quote?

Angie Judge: Oh, go ahead.

Arthur Affleck: So I want to leave us with the words of the great Frederick Douglas. Frederick Douglas said “it is far easier to build strong children than to, than to repair broken men and women”. And so let us together work on early learning on play and play based learning to build strong, healthy, productive children, so we won’t have to try to prepare broken men and women, which doesn’t work so well. So thank you and Angie for your time. And I enjoyed so much talking.

Angie Judge: Likewise, a fantastic conversation. Thank you so much, Arthur.