The pocket guide to retail analytics in visitor attractions
For many visitors, a souvenir from the gift shop carries the visitor’s memory with it long after the ticket stub is lost. To the visitor attraction, retail is not only an important part of the visitor experience but of the per cap revenue too.
Combined with other auxiliary revenue such as dining, photography and parking, these non admission lines of business outside of the experience itself make up an increasingly large portion of earned revenue.
Each of these operations also brings different challenges in their respective business domains, with depth and nuance from data and often the added complexity of sponsors and operating partners, plus for retail – sometimes an ecommerce outlet too. Here, we dissect the top Key Performance Indicators (KPIs) for retail analytics in visitor attractions, metrics to manage in reporting and insights to explore to increase visitor upsells.
Top indicators for retail in visitor attractions:
- Revenue growth
Any analysis on revenue performance should begin with understanding the topline revenue, by line of business, comparison to the prior period and – due to its seasonal nature – yearly growth, including context set back to a pre pandemic baseline if still applicable.
- Per cap growth
Because retail or other auxiliary revenue is largely a follow on function of visitor volume, true growth should be understood by looking at average revenue per visitor and resulting growth rates. This can be especially useful even down to a product level, understanding if the per cap spend on a product line is growing more or less than overall visitor trends.
- Gross margin
Price increases from inflationary pressures make it easy to misinterpret revenue growth as a performance. Looking at margin growth tells a more truthful picture. As most point of sale systems only record the cost of goods sold and the total price, margin will need to be calculated as a transformation for data.
- Retention rate
Ideally, visitor attractions should record a member ID or even ticket holder ID against their retail transactions (often for a discount incentive). This and identified customers through ecommerce allow analysis of the retention rate of consumers in store and online, plus other interesting analysis such as the average onsite and online auxiliary spend per member per year towards Lifetime Value (LTV).
- Visitor happiness
Some retail operators will offer a point of sale based satisfaction survey or post purchase ecommerce review which can be used as a channel in voice of the visitor analysis. Outside of retail specific data capture, general visitor online reviews or exit surveys can also be queried for terms relating to the retail store or other aspects such as dining to understand visitor feedback on the retail moment and its role in the visitor experience.
In addition to summary revenue and average revenue per visit, other metrics to include in a typical retail report:
- Performance against goal
Revenue targets by line of business set all the way down to a daily granularity help focus and motivate front of house teams, including to move specific product lines such as an at the counter basket upsell or for specific staff members.
- Capture rate
Unless guests exit through the gift shop, retail revenue is a function of how many visitors make it into the store (which may also be out of control of the retail manager). Where possible, install footfall counter hardware at the store entrance. Calculating capture rate from the venue visitation into store attendance makes it possible to see to what degree the visitor experience is responsible for retail results.
- Conversion rate
Likewise, by comparing the number of in store shoppers to the volume of retail transactions, the conversion indicates to what degree customers are taken with items on display, price points and accessibility to the counter. In the absence of footfall counters to record in store shoppers, use visitation as a proxy. This rate can vary significantly, especially for in store crowding and is the easiest metric to move to increase revenue.
- Average Transaction Value (ATV)
Dividing retail revenue by the number of transactions gives the average order value or average transaction size. This is an interesting metric to analyze for trends and patterns and the next best metric to move to increase revenue.
- Average basket size
Dividing the number of items sold by the number of transactions gives the average basket size. This is a great metric to use to motivate the retail store team to promote upsells and to monitor during basket size specific promotions.
- Top and low selling items
Monitoring the top or low (or not selling) items, or those with increasing growth rates, helps fuel decisions around which items to promote or showcase versus discount or even discontinue, and future purchasing decisions.
- Other business specific metrics
For example for dining, metrics such as covers (also known as seats or PAX) and average revenue per guest helps complete the picture of how visitors are spending.
When looking for insights from retail analytics in visitor attractions, try:
- Analyzing correlations to crowding in location or in store
- Comparing store retail hours to location popular times
- Contextualizing per cap trends and patterns to who is visiting, such as based on ticket types or visitor origin
- Analyzing exhibition or event specific merchandise over the course of an exhibition
- Checking pop up store cannibalization against per cap spends across the location complex
- Analyzing the performance of various promotions and discounts and their impacts on metrics such as conversion rates and basket size
- Attending to revenue assurance such as checking the use of specific discount codes or the volume of returns
- Comparing ecommerce ship to zip codes with visitor origin for targeted visitor marketing campaigns
- Assessing the influence of weather, seasonality and holidays
- Performing basket analysis to inform tactics such as recommended upsells or cross promotions
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