Retail heatmaps: see how customers move in store

What a retail heatmap shows

A retail heatmap is a floor plan with behaviour on it. Instead of one number at the door, the store appears as zones, each with its own traffic and its own story:

• Hot and cold zones: the areas where visitors linger, and the ones they pass or never reach.
• Visitor paths: the routes people actually take across the floor, first stop, next stop, last stop.
• Dwell by area: how long visitors stay in each zone, separated into a quick look versus a real visit.
• Anchor positions: the zones that pull and hold the most traffic.
• Street to door: passers-by outside and the share the window pulls inside, so the map starts before the entrance.

Bumbee Labs delivers this as zone, flow and path analysis, a richer and more actionable version of the classic heatmap. Rather than a coloured overlay from a single camera, you get movement data for the whole floor, comparable week to week and store to store.

The decisions a heatmap drives

A heatmap earns its keep when it changes something on the floor. Three decisions come up again and again.

Layout. When the busiest route misses the products you most want seen, the answer is in the map. A large Scandinavian retail chain working with Bumbee Labs redesigned the main path in some of its stores once the flow data showed where visitors actually walked.

Campaigns. Hot zones are where a campaign message works hardest. The same chain used its hot zones for campaign messaging, and a flagship can measure what a campaign table, feature wall or brand installation does to traffic and dwell, before and after the change.

Staffing placement. Zone-level peaks show where people are at which hours, so staff stand where visitors flow rather than where habit puts them.

Run many stores and the map multiplies: the same zone metrics in every location make best practice visible and copyable. Run one flagship and the map deepens, from window capture to floor flow and dwell for a single statement store.

How in-store flow is measured anonymously

No cameras are needed for this. Wi-Fi-based people counting uses the access points a store already runs. Phones emit signals as people move, and those signals are anonymised and aggregated into zone statistics. Nothing is asked of the visitor: no app, no login, and no individual is ever identified. AI filtering strips out noise such as stationary devices and staff-like behaviour, and manual control measurements calibrate every installation against reality. It is the only footfall method in Europe approved by a data protection authority, so the map of your floor carries no privacy baggage.

Reading the map honestly

A cold zone is a finding, not a verdict. It might be a layout problem, a product problem or simply the back corner of the building, and the way to tell the difference is context. Set the zone data against the funnel around it, passers-by, capture rate, visits and dwell, and compare like periods with like. The full metric catalogue shows every measure that can sit behind the map, and how each reaches you through dashboards and the API. When the map and the funnel point the same way, the decision usually makes itself.