Site Unseen Podcast EP1: Christian Betov of PB Analytics

How Location Intelligence and Footfall Data Shape Retail Asset Decisions

How do you tell whether a shopping centre is attracting the right customers, a new development will change a city centre, or a tenant mix still reflects local demand? In this episode of Site Unseen, Denise speaks with Christian Betov of Peter & Betov Retail Analytics about the role of location intelligence and footfall data in those decisions.

Christian's starting point is practical: define the decision first, then choose the evidence that can help answer it. A count of visits can be valuable, but it becomes more informative when combined with where people travel from, how long they stay, who they are, and what they say about their choices.

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Start with the decision, then select the data

Christian works with commercial real estate businesses on asset management, leasing and marketing strategy. He describes how different data sources can serve different questions. Mobile location data may show patterns across a catchment and how they have changed over time. On-site sensors or cameras may add detail about activity within a particular asset. Demographic and socioeconomic information can provide context about the people represented in those patterns.

His advice is to choose sources according to the site and the question. An inner-city centre with stations beneath it presents a different measurement challenge from an out-of-town retail park. A high street, mall and individual store may each need a different definition of a meaningful visit. The useful question is: “What do we need to decide, and what evidence will make that decision clearer?”

Look beyond a headline footfall number

Footfall data is a starting point for understanding retail performance. Christian stresses the difference between people passing through a location and people who may actually be visiting to shop. Dwell time can help distinguish these patterns; other sources can add context about how visitors use a store or mall.

Once a reliable visit measure is in place, an asset team can compare performance with relevant competitors and examine changes over time. Christian also discusses a possible “bounce rate”: people who pass a shop, look briefly, or leave soon after entering. These measures do not prove a sale or explain a visitor's motive on their own. They help managers ask sharper questions about the experience an asset offers.

Read changes in the catchment, not just changes at the asset

Christian recounts a shopping centre in Cologne that had not regained its earlier footfall after COVID restrictions. The location data suggested that younger visitors had shifted toward the city centre while older visitors continued to use the mall. The pattern pointed to a specific customer segment worth investigating. Qualitative research, such as surveys and loyalty insights, could then help explain why that change happened and what the centre might do about it.

This is the value of location intelligence alongside footfall data: it can show not only that visits changed, but also where visitors may be going instead and which groups are changing their behaviour. That makes the next decision more specific than a broad push to “increase footfall.”

Test whether a new retail site is a threat or a complement

A new mall, retail park or brand does not automatically take visits from an existing high street. Christian describes a Free Rider Index developed in his team's analysis. Using visitor origins and patterns across competing places, the index is intended to distinguish destinations that attract people to an area from those that benefit from trips generated elsewhere.

For a proposed site, his suggested approach is to compare similar places and examine what happened before and after a comparable opening. That can help city leaders, owners and developers test whether a new destination is likely to compete with existing retail or coexist with it. He points to German city examples where destinations complemented each other rather than acting as direct threats. The comparison is evidence for a decision, not a guarantee of what will happen in a new market.

Use the evidence to adapt leasing and asset strategy

When local preferences shift, the response need not be a complete redevelopment. Christian argues that landlords can review leasing, tenant mix and marketing against the current catchment. A retailer nearing a lease decision may ask whether the local customer base still fits its offer. An owner may ask whether different brands or uses would better serve the visitors the asset can attract.

He also makes a case for bringing analysis into an asset management pitch. A manager who has already examined an asset's visitors, competitors and opportunities can arrive with an informed short- and medium-term strategy. Even a focused first analysis can make the proposed plan more concrete.