Fuel and convenience-store brands use catalog.xmap.ai to map every station on a highway corridor, track a competitor's new site the month it opens, and choose the next location by traffic, not guesswork.
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.
Fuel volume is driven almost entirely by traffic and access, the site is the strategy.
EV-charging sites now compete for the same dwell-time customer as a traditional station.
Station buildouts are expensive and hard to relocate, the site-selection call has to be right the first time.
See every fuel brand along a highway or arterial corridor, with traffic score attached.
Catch a competitor breaking ground on a new site before it opens, from monthly refreshed data.
Rank candidate parcels by nearby traffic, competing brands, and access points.
See which fuel brands dominate a region and where a challenger brand is under-represented.
Identify corridors with fuel demand but no charging infrastructure yet.
See what food and retail brands already sit alongside a fuel site to plan a c-store offer.
Station count by brand along a 40-mile stretch.
Every export carries 36 columns; these are the ones fuel-retail teams use most.
| Field | Type | Why it matters here |
|---|---|---|
| brand_name / chain_flag | string / boolean | Identifies which fuel brand operates each site |
| latitude / longitude | float | Places every station precisely along a corridor |
| traffic_score | numeric | The single strongest predictor of fuel volume at a site |
| category_level_3 | string | Distinguishes fuel stations, EV chargers, and convenience-only sites |
| hours_of_operation | string | Flags 24-hour sites versus limited-hours competitors |
| open_status | string | Flags new station openings and closures for monthly monitoring |
| venue_hierarchy | string | Shows what convenience or food brands co-locate at a site |
| dwell_time | numeric | Signals c-store or food attach potential at a fuel stop |
A fuel retailer is evaluating a highway corridor for a new flagship site. The team exports every existing station with traffic score and brand, finds a 12-mile stretch with no competing brand and strong traffic, and moves it to the top of the site-selection shortlist the same day.
We'll pull a live sample for your category and market.