Gym and fitness-studio chains use catalog.xmap.ai to map competing clubs and studios in a catchment, track a rival's new opening, and score candidate sites by nearby residential density and competing formats.
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.
A catchment can support several formats at once, or be saturated in just one of them.
Fitness catchments are tight, so getting the local read right matters more than most retail.
Studio build-outs are capital-intensive, so the site-selection call needs to be right upfront.
See every gym, studio, and health club within a candidate site's realistic membership radius.
Catch a competing chain's new location as soon as it appears in a monthly refresh.
Spot catchments saturated in big-box gyms but missing a boutique or budget format.
Weigh a candidate site by nearby apartment complexes and office density that feed membership.
Find hotels and residential buildings with existing fitness amenities worth a partnership pitch.
Check a proposed new studio against your own network before approving it, to avoid cannibalization.
Facility count by format within a 3-mile membership radius.
Every export carries 36 columns; these are the ones fitness teams use most.
| Field | Type | Why it matters here |
|---|---|---|
| category_level_3 | string | Distinguishes big-box, boutique, budget, and hotel/apartment fitness facilities |
| brand_name / chain_flag | string / boolean | Separates national chains from independent studios |
| latitude / longitude | float | Drives every membership-catchment and drive-time calculation |
| open_status | string | Flags new gym and studio openings and closures for monthly monitoring |
| rating / review_count | numeric | Signals which nearby facilities members already prefer |
| hours_of_operation | string | Reveals 24-hour access gaps in a catchment |
| venue_hierarchy | string | Identifies hotels and apartment complexes with in-building fitness amenities |
| dwell_time | numeric | Signals how long visitors typically stay at a facility |
A fitness chain is evaluating a growing neighborhood for its next studio. The team exports every gym and studio within a 3-mile radius, sees big-box gyms are saturated but boutique formats are scarce, and greenlights a boutique-format studio instead of the big-box location originally scouted.
We'll pull a live sample for your category and market.