Foot Traffic

Also available at other cadences:Hourly Weekly Monthly

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.

Available in:Finland Norway Sweden

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 captures short-horizon activity: event days, openings, promotions, weather effects, and within-day or day-of-week patterns. Each row is a single period, with no period total or typical-day median.

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; each row is a single day or hour, so compare equivalent periods.
Visitor types. Visits split into people who live in the area (residents), people who work there (workers), and everyone else (other visitors), which separates genuine visitation from the resident and worker baseline. These groups can overlap, a person can be both a worker and a resident at the same location, so the parts need not add up to the total; the total is the most reliable figure.
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.

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.

Schema

This is the standard schema for the metric. Always check the schema on the specific dataset you're using, since small variations may occur per country, map, or cadence. See the list of datasets using this metric below.

Map columns (e.g. ZIP code, state, brand, polygon) are usually exposed on each dataset as available columns that aren't included by default. They're not listed here because each dataset is connected to a different map and therefore has a different set of map columns available. Open a specific dataset below to see its full schema.

Column	Type	Description
location_id	STRING	Unique identifier of the location.
observation_start_date	DATE	Start of the observation period.
observation_end_date	DATE	End of the observation period.
visits_sum	INTEGER	Estimated sum of unique people per day at the location over the period; a person who visits on several days is counted on each day.
non_resident_non_worker_visits_sum	INTEGER	Sum of the daily counts of visitors who neither live nor work in the area.
resident_visits_sum	INTEGER	Sum of the daily counts of people who live in the area, over the period.
worker_visits_sum	INTEGER	Sum of the daily counts of people who work in the area, over the period.

Datasets using this metric

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