Convenience-store chains (standalone from fuel retail) use catalog.xmap.ai to map competing c-stores at a hyper-local level, track new openings, and find the walkable-catchment gaps worth a new box.
See every c-store within a short walk or drive of a candidate site.
Catch a competitor's new box the month it opens, from monthly refreshed data.
Weigh a candidate site by nearby foot traffic and residential density.
Site near transit stops and office clusters that drive quick-trip demand.
catalog.xmap.ai is a self-serve database of 140M+ real business locations across 40+ countries. Every record is an actual, physically-located business (not an estimate) with up to 36 structured fields: name, full address, latitude/longitude, category (three levels deep), brand and chain affiliation, hours of operation, phone and website, star rating and review count, open/closed status, and more.
You filter the catalog by category, brand, or geography in a live web interface, watch the matching record count update as you narrow the search, and export the results as a clean CSV file, ready to open in a spreadsheet, load into GIS software, or join against your own data.
The dataset refreshes every 30 days, so an export reflects recent openings, closures, and changes rather than a static snapshot from years ago.
| Field | Type | Why it matters here |
|---|---|---|
| latitude / longitude | float | Powers precise walkable-catchment and drive-time calculations |
| hours_of_operation | string | Reveals 24-hour access gaps in a hyper-local trade area |
| traffic_score / dwell_time | numeric | Signals quick-trip demand at a candidate corner |
| open_status | string | Flags new c-store openings and closures for monthly monitoring |
A c-store chain exports every competing store within a dense downtown grid, finds a six-block stretch with no 24-hour option, and opens its next location there.