Nearest store with Atlases now live

You can now manage location data — stores, branches, dealers, service areas — as a first-class resource with Atlases, and output each person's nearest location directly in a Pipeline payload.

Previously, proximity required stitching together a Dataset and a Place. Atlases follow the Dataset pattern instead: create one from a hosted CSV or an existing connection, map your locator columns (address + postcode, lat/lon, or GeoJSON/WKT geometry), and define properties you can filter on later.

In the Pipeline configuration page, a new Nearest location control under Payload adds Location name, Location reference key, and Location distance (m) to your deployment. Advanced settings let you restrict to specific Atlases, filter by location properties, and choose between the nearest location or every location that qualifies. Radius cohorts and market opportunity analyses can now be built from Atlases as well.

Via the API, use POST /atlases with output_to_locations, and the new location property on a Pipeline's payload. If you use select: all, you must supply a max_distance — otherwise every location is returned for every person. See the Atlas API reference to get started.