How people really move
Field notes and research on footfall: which way shoppers turn, why queues empty a store, what the weather does to a high street, and how anonymous counting turns all of it into decisions.
Insights
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Counting without cameras
People counting without cameras: Wi-Fi turns existing infrastructure into an anonymous sensor. No new hardware: how passive signals become footfall data.
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Desire lines
Desire lines are shortcuts worn into grass and pavements. Indoor desire lines show on a retail heatmap, revealing where people go versus where design intended.
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Left or right?
The 'invariant right' says shoppers turn right; counterclockwise stores turn them left. Which is true? What footfall path data really shows.
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Counterclockwise layout
Most supermarkets route shoppers counterclockwise. Direction matters less than loop design and sightlines. Path analytics shows what your shoppers really do.
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DOOH audience measurement
DOOH audience measurement with real footfall data: impressions, reach and exposure-minutes per screen. What the numbers can (and honestly cannot) tell you.
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Footfall vs sales
Traffic up, revenue flat, or the reverse. The gap between them is in-store conversion rate: the retail performance metric most teams need most and track least.
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MAC randomisation
MAC randomisation was meant to stop Wi-Fi tracking. Research shows it can be worked around, which is why real privacy rests on architecture, not addresses.
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Museum attendance in numbers
Museum attendance in numbers: what official statistics say about visits, the definitions that decide the figures, and what the trend means for reporting.
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Museum dwell time
Wi-Fi analytics shows which exhibits hold visitors and where queues build. Even flagship galleries can average under four minutes' dwell. Anonymous throughout.
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Crowd flow
Crowd bottlenecks follow predictable patterns. Crowd density data and crowd management alerts let you act on a pinch point before it becomes the headline.
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Real-time occupancy
Live occupancy counting started as a pandemic fix. Venues that kept it found real-time occupancy monitoring and capacity management useful well past the limit.
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15-min city
The 15-minute city is a planning ideal. Urban footfall analytics and pedestrian flow data show whether a neighbourhood functions as one, or where the gaps are.
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Decompression zone
Every shopper walks through the store entrance zone; almost none see it. Retail anthropology named the decompression zone, measured the cost, and found the fix.
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Footfall calendar
The retail footfall calendar repeats every year. Measuring seasonal footfall patterns lets you plan against real data, and January stops catching you out.
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Forecourt funnel
Most drivers who refuel never enter the shop. Footfall data maps pump-to-store conversion and capture rate, showing exactly where the forecourt funnel leaks.
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Gruen effect
Victor Gruen designed the shopping mall as civic space, then disowned it. The Gruen transfer: how retail design turns disorientation into the impulse buy.
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Weekly rhythm
Every space has a repeating weekly visitor pattern. Footfall-based staffing from measured data serves the one that actually shows up, not the one you assumed.
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Benchmarking footfall
Footfall benchmarking sounds simple. The trap is comparability: same method, same definitions, same calibration. What makes a footfall benchmark credible.
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What is a probe request?
A probe request is the short signal your phone sends to find Wi-Fi networks. How it works, why it matters for privacy, and how counting uses it.
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Weather and footfall
Rain suppresses high street footfall while covered destinations gain. Measured baselines separate genuine trading weakness from weather noise you can't control.
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Catchment analysis
Catchment area analysis reveals where visitors really come from, district by district, and why it reshapes site selection, marketing spend and tenant mix.
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Boomerang rate
Many shoppers enter, walk a few metres, then turn back. This 'boomerang rate' starves rear zones of floor traffic and store penetration. Here's what drives it.
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Every space tells a story in the way people move through it: the direction they turn at the door, the corners they never reach, the minutes they linger, the moment a queue makes them give up. These pieces look at what that movement reveals, and how privacy-first footfall analytics turns it into data you can act on.