Roamers Foot Traffic
Foot traffic from international visitors, broken down by country of origin, for measuring tourism and cross-border demand.
What does this metric tell me?
This metric estimates visits from international visitors, people whose home is in another country, using the same idea of a visit as domestic Foot Traffic. Totals are reported for all international visitors and broken down by their country of origin.
Counts are estimates of international visits, not a census.
What questions does it answer?
- How popular is an area or attraction with international visitors, and is that growing?
- Which countries do those visitors come from, and how does that mix vary by destination?
- How seasonal is international demand here?
- Did a campaign aimed at a specific country move visits from it?
Reading this cadence
Reported monthly. The month lets the same visits be re-expressed along independent views, day versus night and weekday versus weekend, so you can see when international demand concentrates.
How it's produced
International visitors are identified and attributed to a country of origin, then aggregated into visit estimates per location and origin country.
How to read it
- Country rows are not exhaustive. Each row is one origin country, shown only when it is large enough to report, so summing the country rows understates the true total.
- Two separate splits. Daytime and nighttime split the visits one way; weekday and weekend split them another. Each split adds up to the total on its own, so do not mix columns from different splits.
- A confidence score and a baseline-relative index (visit_index), where present, help you judge reliability and compare against a norm rather than reading raw counts.
Related metrics
- Foot Traffic, total footfall including domestic visitors.
- Visitor Journey, where these visitors go before and after.
Country- and dataset-specific behaviour (coverage, geography units, exclusions, how international visitors are identified, 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. |
| nationality | STRING | Country of origin of the international visitor. |
| iso3 | STRING | ISO-3 code of the visitor's country of origin. |
| 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. |
| visits_daytime_sum | INTEGER | Visits occurring during the daytime between 07:00–16:59. |
| visits_nighttime_sum | INTEGER | Visits occurring during the night between 17:00–06:59. |
| visits_weekday_sum | INTEGER | Visits occurring on weekdays. |
| visits_weekend_sum | INTEGER | Visits occurring on weekends. |
| confidence_score | FLOAT | Relative reliability of the estimate; lower for low-activity locations. |
| visits_index | FLOAT | Visits relative to a baseline. |