Deloitte, Bain, BCG-style advisory teams use catalog.xmap.ai to build competitive-landscape and market-entry deliverables in minutes instead of waiting on a legacy data vendor's sales cycle.
Map every existing competitor and adjacent business in a target market before recommending entry.
Build the "who's already there" section of a strategy deck with live ratings and category data.
Identify categories underrepresented in a submarket to support a growth thesis.
Validate a target company's footprint claims against an independent dataset.
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 trade-area export ranked by competitor count per category.
| Field | Type | Why it's in the deck |
|---|---|---|
| category_level_1–3 | string | Slices the market into the categories a client competes in |
| brand_name / chain_flag | string / boolean | Separates chain competitors from independents |
| rating / review_count | numeric | Signals competitor performance without a client survey |
| open_status | string | Flags recent openings and closures for momentum slides |
An analyst filters the catalog to the client's category within a target metro, exports every competitor with ratings and traffic signals, and hands the modeling team a clean CSV the same afternoon.