Measure what makes your retail destination pull

The job to be done

You run or own an external retail destination (a retail park, an out-of-town cluster, a big-box power centre) where separate stores share one location, one car park and one reputation as a place worth visiting. The questions are about the destination as a whole and the relationships inside it: Where do visitors travel from, what’s our real catchment, and how far does our pull reach? How many people does the destination draw, when, and how is that changing? Which tenants are true anchors that pull traffic to their neighbours, and which are “false anchors” that visitors come to and leave? How much cross-shopping actually happens between stores? What’s a unit worth, given the footfall it gets and generates? How do we set footfall-based terms, attract the right tenant mix, and get stores cooperating to lift the whole place? Sales per tenant won’t answer any of that. It misses the flows between them.

Measuring the destination as one system

Bumbee Labs measures the destination as a system: Wi-Fi at entry points, the car park approach and key tenants captures footfall and flow on site, and cellular (4G/5G) network data extends the picture to the wider catchment, where people come from and where they go beyond the destination. You don’t need to cover every metre: entry/exit points and anchor locations are usually enough, because an anonymous alias is recognised again as a visitor reaches the next measured zone. And because this is the only footfall method in Europe approved by a data protection authority, a destination-wide rollout carries no privacy risk.

How hybrid Wi-Fi + cellular counting works →

What data you get

• Catchment and origin: where visitors travel from and how far the pull reaches, using cellular data for the macro environment beyond the site.
• Total footfall to the destination, on adjustable time scales, plus visits to individual tenants and clusters.
• Cross-shopping and zone correlation: where people go after a given store, which anchors generate visits to their neighbours, and which are “false anchors”.
• Capture rate: how many pass a unit versus enter it.
• Dwell time and visitor paths across the destination: the routes people actually take between stores and the car park.
• Footfall-based value per unit: the traffic each location gets and generates, as the basis for rents, tenant mix and leasing.
• Peaks, trends and event impact: for shared staffing, marketing and managing busy periods.

The same catchment evidence carries over when you weigh the next location; see site selection analysis.

→ See all metrics and delivery formats

Proof from multi-tenant places

Across any multi-tenant area, footfall analytics turn assumptions about prime spots and anchor pull into fact, often overturning which locations are really the busiest and which activities lift the whole place rather than a single unit. A retail destination puts the same catchment, flow and cross-shopping evidence behind its own tenant mix and value.

See how movement data reshaped a city centre →

Where this fits

An enclosed shopping centre (with its food court, internal mall and screens) is run differently; that operator playbook is on mall operators & property owners. The catchment and movement methods a destination relies on are the same ones used for city centres & smart cities, and the tenants inside your destination are themselves retail chains that benefit from in-store footfall data.