Foot Traffic Month
Foot Traffic on Places
The number of visits to a location over a period, the foundation metric for how busy a place is and how that changes over time.
What does Foot Traffic tell me?
Foot Traffic estimates how many visits a location receives during a period. It is the foundation metric for human-mobility analysis: how busy a place is, how that rises and falls over time, and how one location compares to another.
A daily count is the number of unique people at the location that day. Longer cadences sum those daily counts over the period, so a person who comes on several days is counted on each of them, and the period total is not a unique-person count. Figures are estimates calibrated to real-world volume, not a census.
What questions does it answer?
- How busy is this location, and is it trending up or down?
- How does footfall compare across my sites or against nearby locations?
- How did visits respond before, during, and after an event or campaign?
- What is this location's share of activity in its wider area?
- How seasonal is demand here?
Reading this cadence
This cadence is for trend and seasonality work. It adds period-level summaries, a total of visits across the period and the typical single day within it, that absorb day-of-week noise and make period-over-period and year-over-year comparison meaningful.
How it's produced
Foot Traffic is modelled from an aggregated activity signal, corrected for how much of the population that signal represents, and calibrated so the output reflects real-world visit volume.
How to read it
- Compare like for like. Use the same cadence and comparable periods. The typical-day figure (the median daily count) is a per-day value, so it is comparable across periods of different length; the period total grows with the number of days in the period.
- Low counts are noisy, and a zero can mean "too little activity to report here," not "nobody came." A confidence indicator, where present, flags rows that are less reliable.
Related metrics
- Visit Length, how long those visitors stayed.
- Trade Areas, where those visitors came from.
- Visitor Demographics, who those visitors are.
Country- and dataset-specific behaviour (coverage, geography units, exclusions, release timing) is documented on each dataset in its country catalog.
Related techniques
The techniques applied to the signal behind this dataset.
Home & work inference
Estimating the likely home and work areas of visitor groups, always at area level and never an address, to enable resident / worker / visitor breakdowns, trade areas, and visitor-only scoping for Visit Length.
Extrapolation
Scaling the observed sample of devices up to population-level visit estimates, so counts reflect real-world volume rather than sample size.
Privacy approach
Pine59 products are built for statistical use only, and no output can be linked to an individual person.