Visitation growth is the primary driver behind the decision to adopt analytics in most visitor attractions. For some, it is an attempt to reverse declining numbers or deal with a challenging scenario, such as a temporary partial closure for renovation. At the other end of the scale, those who have mastered the growth engine look to reinforce continuous achievement of solid double digit growth, year on year. Many fall somewhere in between, their recent memory including a few stellar years alongside troubling ones – fluctuations which leave management determined to achieve predictable, repeatable growth.
Embarking on the journey of becoming data informed – with its natural focus on the numbers – is a step in the right direction to get more visitors. But to really push the needle, here we take a look at our favorite strategies.
1. Get the fundamentals right
The most instant way analytics increases visitorship is by shining a light on its accuracy. Where operations are replacing inaccurate manual clickers, or transitioning away from relying on ticket counts that do double duty as visitation, we find visitation rates jump by around 20% in simply introducing a proper automated electronic footfall counting mechanism on every public entrance (another common gap is when counts are made from a main entrance, yet groups instructed to enter through a side door).
Even with the right hardware, device failures (such as footfall counters going offline) or procedural misuse (such as ticketing switching to an unprocessed method) can otherwise go undiagnosed, which a closer eye on the numbers often reveals. An easy remedy for a day missing visitation data in these scenarios is to use the forecast as a proxy number.
For venues who opt to continue relying on ticketed admissions as visitation, data integrity inspections as part of an analytics rollout commonly reveal errors in legacy report queries caused by ticketing system complexities.
The challenge in accepting growth from improved data integrity is one of optics – how to message a sudden spike in visitation, whether to embrace it gradually or at once, then how to consider year on year performance against historic records. Albeit a gain on paper rather than in actual visitors, it is an important checkpoint for procedures that may have remained untouched for decades and an opportunity to emphasize the importance of data for those at the coal face of visitor service.
In Dexibit, refer to visualization 123 to compare and audit footfall and admission measures.
2. Back to the basics
When it comes to introducing experimental change, many attractions begin by examining opening hours and days. The beauty of analytics is the ability to easily see popular times and days to begin informing a case for change, then track agile experiments for instant feedback – importantly, while being able to gauge seasonal subtleties. Anecdotal beliefs around opening hours are frequently shaped in a specific season, and don’t necessarily apply year round.
Rather than guess, it’s much better to analyze the detail and do the math. If the venue closes for a day or two each week – what is the opportunity cost in visitors tallied each year? If it were to open earlier or close later, what then? Should the venue host late nights, and if so, on which week day? What about after hours events?
In Dexibit, refer to visualization 66, 75 and 89 for opening hours analysis.
3. Getting in the door
Next comes a valuable exercise in investigating one of the most important, yet overlooked segments of the visitor experience: entrance. If multiple entrances are used, analytics enables comparison between them. If the main entrance to the campus then requires a ticketed admission further into the venue proper, what is the revenue assurance, or the missed opportunity of visitors who don’t convert? If alternate facilities, such as gardens, cafes or shops are frequented by the non visiting public, what is the conversion rate to the venue proper, and how can it improve over time? Understanding the street appeal, interior entrance or secondary conversion experience in the visitor journey makes big gains because it takes one of the biggest hurdles to growth out of the equation – the challenge of physically getting visitors onsite.
Depending on the venue’s circumstance, this might also involve understanding visitor satisfaction around queue wait times for entry and any lost opportunity of those who turn away at their appearance.
Sometimes, this conversation over entry extends to how visitors get to the venue. This might include thinking about a shuttle to port visitors from a high traffic tourist area nearby, or how to take the ticket box office to the visitor locations offsite, usually via a booking agent.
In Dexibit, refer to visualization 99, 117 and 118 for entrance analysis, 88 for admission assurance, 107 for cross zone conversion and 40 for channel sales.
4. Maximize capacity by managing attrition
When managing extensive crowds, even if only during the high season or for a select exhibition, limitations on capacity will throttle visitation. Unless this is a purposeful tactic (for example, to warrant exclusive pricing, promote a premiere experience or divert growth to membership), inevitable attrition (advance ticket holders who don’t show up) can be predicted using machine learning, enabling the venue to issue overage (issuing more tickets than capacity otherwise allows – a common technique for airlines and hotels). These artificial intelligence models can also point to how to reduce attrition too, commonly through reducing the lead time of advance bookings, to ease the operational burden. Maximizing a venue’s limited capacity naturally yields higher visitation.
In Dexibit, refer to visualization 119 for admission performance for attrition, in addition to the attrition forecasting model.
5. Machine learning informed product development
Machine learning models use a series of featured factors which provide insight on the comparative influences on visitation. These could include elements such as seasonality, months, days of the week, school terms, public holidays, public programming, regional events and even the weather. Understanding what impacts visitation in a positive or negative fashion and to what degree helps make important decisions about where to focus product development investments and efforts, plus the importance of go to market timing over the course of the year. For example, it may be that cruise ships present an untapped organic boost which could be further explored through specific offers throughout the summer season, or that September’s Saturdays might benefit from a price promotion, coinciding with the school holidays to exaggerate the uplift during this period.
In Dexibit, refer to visualization 102, 103, 105, 106 and 114 for analysis of various internal and external influences (using calendar controls to evaluate seasonal differences) in addition to the visitation forecasting model.
6. Using residuals to mitigate and capitalize
Forecasting provides more than a preview of what’s coming – it also provides hidden cues to help growth hack visitation. By looking back retrospectively at how forecast visitation compares to actual, the difference between the two (known as the ‘residual’) points to unforseen influences. Keeping an eye on these residual values from day to day to look for high or low outliers provides an indicator of negative factors to mitigate against or positive factors capitalize upon, whether these be within or outside of the venue’s control. In particular, this analysis can be used as a proxy for marketing attribution – for example, seeing if new billboard advertising achieves higher than usual attendance figures during the campaign, or if new brand message is achieving cut through. Once an uptick is evident, doubling down on marketing investment as its return continues to be witnessed paves the way for accelerated growth.
In Dexibit, refer to visualization 140 and 141 for forecast versus actual visitation and the resulting residual, in addition to the various forecasting models.
7. Using digital correlation to answer the intricacy of online return
Whilst offline marketing has traditionally been difficult to attribute, the world of digital marketing natively incorporates a high degree of analytics. However, other than measuring ecommerce ticketing, it is challenging to otherwise determine the relationship between online advertising and onsite visits, or to assess the return on investment for digital. Now, using Dexibit’s new digital correlation forecasting model, it is possible to analyze the strength and lag between a visitor’s online interaction and their onsite visit, even slicing these by region and channel. This data can be used for advertising scheduling to maximize the digital marketing spend, whilst designing and scheduling content that results in a higher conversion to onsite visitation.
In Dexibit, refer to visualization 20 for onsite versus online base correlation, in addition to the digital correlation forecasting model.
8. Creating loyalty through value
Many venues have a reasonable degree of repeat visitation, yet it is a segment previously invisible to operations, given the complexities of measurement. Now, using WiFi data, repeat visitor rates can be measured and compared to member check ins (any gap representing a target to close), alongside other correlations. Factoring in measured improvements to visitor satisfaction, sentiment and dwell time are also an important part of the picture. Growing this loyalty and conversion through focusing on value in experience design, marketing promotions and visitor service all aids overall visitorship.
In Dexibit, refer to visualization 84 and 85 for repeat visitors, 100 for member conversions, 155 and 156 for member visits, 125 and 35 for visitor satisfaction, plus 41, 73, 74, 96, 97 and 98 for dwell time and its distribution.
9. Setting goals (and incentives)
An important tactic in using analytics for the growth agenda is the act of setting Key Performance Indicators (KPIs), measuring goal burn and importantly, rewarding staff achievements. A performance framework might include organizational wide goals alongside department specific targets, cover both long versus short term objectives and balance team plus individual rewards. Regularly communicating targets, goal burn and rewards at every leadership opportunity is key to their effectiveness.
In Dexibit, refer to visualization 104, the performance gauge on each primary volumetric or the targets tab of venue management.
10. Scenario simulation
If the venue’s business model includes the use of exhibitions, deciding on the selection, scale and schedule of these will have a significant impact on top line annual visitation. Using machine learning, we can now not only uniquely forecast exhibition performance, but simulate such, evaluating side by side scenarios to look at various start and end dates for maximizing visitation, durations which optimize waning, alongside tips for price elasticity and budget plateaus. Whilst the decision of which exhibitions to host will likely be a strategic decision far above any pure visitation objective, these forecasts provide an ability to support this decision process of which exhibitions to run, when and at what price or marketing budget, by imagining various scenarios in order to ensure visitation growth is front of mind.
In Dexibit, refer to visualization 122, 139, 124, 137 and 138 for exhibition analysis in addition to the exhibition forecasting model.