Retail Destination speaks to retail analytics expert HoxtonAi’s chief operating officer, Duncan Mann, about utilising footfall counting data
What is the most valuable analytics data retail property landlords should be gathering that they can pass on to prospective tenants and compare across their portfolio of sites?
Tenancy rates should correlate with the value of the site to a store. Value can be driven from the type of customer in the area, the prestige of the area, the amenities of the asset, the quality of the asset operators. Most are hard to measure, so one proxy often used is store revenue, but this can penalise well-run stores for their success. The fairest, most measurable and comparable proxy is simply people: how many people walk past the store front. You can’t sell to them if they aren’t there.
Moreover, understanding the behaviour of these visitors – when they visit, direction of travel, how predictable etc – gives clear indicators of the type of shopper they are. The landowner can compare across different retail assets and begin to build a picture of the visitor behaviours that drive successful assets.
They can measure the impact the capex has on the asset, efficacy of campaigns and initiatives and assess how diversified the portfolio is, which may eventually help inform the type of asset hey want to sell and buy. In turn, they will then have the option of sharing this data with tenants for more transparency where appropriate.
HoxtonAi has an external tool for tracking the footfall of people walking past a store, i.e. not going in – can you tell me a bit about this and explain what this information is useful for?
A store’s value is just as much about getting the message out there as selling at the till. In such a world, the value of the store is in eyeballs and passing traffic and ability to pull people in off the street. How can you measure that without knowing how many people were on the street in the first place? We have a plug and play solution that accurately counts people walking right and left past your store rather than just trends based on phone data.
Do you think landlords and tenants should share their analytics data?
Yes, because if the data is accurate, it builds trust and transparency. Ultimately, both the landlord and retailer want the same thing, a vibrant successful tenant mix drives higher value for the landlord.
How important would you say accurate analytics data is when it comes to decision making for retailers and landlords? Why?
Businesses already base almost all their decisions on data: their takings and financials. Having access to data further up the customer funnel – such as quantum of passing traffic and number of people in the store – helps to explain the ‘why’, and to make the changes quicker. Perhaps the retailer won’t have to wait until the year end to find out their window displays aren’t working, for example. Or that a dip in performance was not due to the proposition, but due to inclement weather driving shopper numbers down. Ultimately, this will not only enable the better decisions, but quicker decisions too.
