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
-
Counting without cameras
Wi-Fi people counting turns a building's existing network into an anonymous sensor. No cameras, no new hardware: how passive signals become footfall data.
Learn more → -
Desire lines
Desire lines are the shortcuts people wear into grass and city pavements, revealing how people actually move. Why that matters indoors as much as outdoors.
Learn more → -
Left or right?
The 'invariant right' says shoppers turn right; counterclockwise stores turn them left. Which is true? What footfall path data really shows.
Learn more → -
Counterclockwise layout
Most supermarkets route shoppers counterclockwise. The claim: left loops lift dwell and spend. The evidence is more complicated, and more useful, than the rule.
Learn more → -
Museum dwell time
Dwell time and visitor flow reveal which exhibits truly engage, where queues build, and how layout shapes the visitor experience, without identifying anyone.
Learn more → -
Footfall vs sales
Traffic up, revenue flat, or the reverse. The gap between footfall and sales is conversion rate, the metric retailers track least and need most.
Learn more → -
Crowd flow
Crowd bottlenecks in transit hubs and arenas follow predictable patterns. Density data and early alerts let you act before the pinch point becomes the headline.
Learn more → -
Real-time occupancy
Live occupancy counting started as a pandemic compliance fix. Venues that kept it running discovered the use cases extended well past the capacity limit.
Learn more → -
15-min city
The 15-minute city is a planning ideal. Footfall data shows whether a neighbourhood actually functions as one, or where the gaps are. Here's how to measure it.
Learn more → -
Decompression zone
Every shopper walks through your entrance zone, almost none of them see it. Paco Underhill named the decompression zone and measured the cost. Here's the fix.
Learn more → -
Footfall calendar
The retail footfall calendar repeats every year. Plan against measured data, not last year's gut feel, and January stops catching you out.
Learn more → -
Forecourt funnel
Most drivers who refuel never enter the shop, but the shop is where the margin is. Footfall data shows exactly where the forecourt-to-store conversion funnel leaks.
Learn more → -
Gruen effect
Victor Gruen designed the shopping mall as a civic space, then disowned what it became. How deliberate disorientation turns an errand into an impulse trip.
Learn more → -
Weekly rhythm
Every physical space has a repeating weekly footfall pattern. Staffing built on gut feel serves the pattern you imagined, not the one that actually shows up.
Learn more → -
Benchmarking footfall
Footfall benchmarking sounds simple. The traps are in comparability: same method, same definitions, same calibration. What makes a benchmark credible.
Learn more → -
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.
Learn more → -
Catchment analysis
Catchment analysis reveals where visitors really come from, district by district, and why it reshapes site selection, marketing spend and tenant mix.
Learn more → -
DOOH audience measurement
DOOH audience measurement still leans on estimates. What real footfall and cellular data can, and honestly can't, tell you about who sees a screen.
Learn more → -
Boomerang rate
Many shoppers enter, walk a few metres, then turn back. This 'boomerang rate' starves rear zones of traffic. Here's what drives it and how to fix it.
Learn more →
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.