Pharmacy and health-retail chains use catalog.xmap.ai to map proximity to clinics and hospitals, track competitor openings, and find trade areas where healthcare access outpaces pharmacy coverage.
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 pharmacy near clinics and hospitals captures demand a standalone location never sees.
Convenience and same-day pickup are now the differentiator against mail-order pharmacy.
Deciding which locations to keep, close, or relocate needs a clear read on nearby coverage.
Rank candidate sites by distance to clinics, hospitals, and medical offices.
Catch a rival chain's new pharmacy the month it opens, from monthly refreshed data.
Find neighborhoods with healthcare demand but no pharmacy within a reasonable distance.
Decide which locations to consolidate by seeing overlap between nearby stores.
Identify strip-mall and shopping-center sites already anchored by a medical tenant.
Choose locations that maximize convenience against mail-order competition.
Share of nearby clinics within a 10-minute drive of a pharmacy.
Every export carries 36 columns; these are the ones pharmacy teams use most.
| Field | Type | Why it matters here |
|---|---|---|
| category_level_1–3 | string | Separates pharmacies from clinics, hospitals, and other health categories |
| latitude / longitude | float | Drives every proximity-to-care and drive-time calculation |
| brand_name / chain_flag | string / boolean | Separates national chains from independent pharmacies |
| hours_of_operation | string | Flags 24-hour and extended-hours competitive gaps |
| open_status | string | Flags new pharmacy openings and closures for monthly monitoring |
| traffic_score / dwell_time | numeric | Signals convenience and accessibility of a candidate site |
| venue_hierarchy | string | Shows co-location with medical offices or shopping centers |
| rating / review_count | numeric | Signals which nearby providers patients already prefer |
A pharmacy chain is deciding where to open next. The team exports every clinic, hospital, and existing pharmacy in three candidate metros, finds one suburb with a dense cluster of clinics and no pharmacy within a 10-minute drive, and prioritizes it over two sites the field team had originally proposed.
We'll pull a live sample for your category and market.