The United States Retail POI Dataset delivers precise lat/long coordinates, verified brand attribution, and update timestamps across retail locations nationwide, purpose-built for trade area and proximity analysis. For the first time, you can confirm a competitor or co-tenant is still operating before the deal is done.

Most data vendors sell you a national license to millions of records you will never contact. BigGeo works differently.You tell us where you sell, and we cut you exactly that geographic slice of the dataset. A single city.
A cluster of ZIP codes. A metro area. A county. Whatever matches your territory. The result is a lean, CRM-ready file containing only the companies in the markets you actually work, delivered at a fraction of the cost of a full national license.

Every trade area model is only as good as the underlying location records. Most retail POI data in the market is months out of date, missing brand context, or imprecise enough to introduce material error into catchment and proximity calculations. Brokers and developers are making seven-figure site decisions on data that was never built for underwriting rigor.
Every record carries exact lat/long coordinates, not street-segment approximations. That precision is what makes sub-half-mile trade area rings and drive-time catchments analytically defensible rather than directionally approximate.

Each location is attributed to its parent brand and concept, so you can segment by chain, filter by category, and answer co-tenancy questions in seconds instead of manually reconciling store names from three different source lists.

Every record carries a timestamp indicating when it was last verified. You can filter to recently confirmed locations before running a proximity analysis, which means your underwriting model reflects the retail environment as it actually exists today.

Coverage spans retail locations across the United States, giving you a consistent data layer whether you are evaluating a single candidate site or running a portfolio-wide gap analysis across multiple markets simultaneously.

BigGeo AI is available today inside ChatGPT and shipping in Claude, giving your team direct access to this dataset through plain language queries with no GIS software and no analyst bottleneck. Instead of waiting for a data pull to answer a competitor density question, you ask it the way you would ask a colleague and get a precise, data-grounded answer in seconds. The underlying location data never leaves the governed compute path, regardless of how you access it.
Every record in the dataset includes an update timestamp that tells you exactly when that location was last verified. Within BigGeo's DataLab, you can filter your analysis to only include records verified within your chosen time window, so your proximity model is built on confirmed operational locations rather than historical snapshots.
Yes. DataLab is where your uploaded data and purchased datasets like this one live, combine, and become spatially queryable together. You bring your candidate site coordinates, and the retail POI layer is already indexed and ready for proximity and catchment computation the moment you activate it. No preprocessing, no ETL work.
Coordinate precision matters enormously at sub-half-mile radii because even small geocoding errors shift which locations fall inside or outside a ring. This dataset uses rooftop-level lat/long coordinates, not street-segment centroids, which is the minimum standard for analytically defensible trade area modeling at the distances retail site selection actually uses.
No. The dataset is indexed on BigGeo's spatial compute engine the moment it is activated, and queries run at sub-second speed without any GIS tooling or specialist configuration. Your analysts can query through BigGeo AI in plain language, build views in DataScape, or access the data programmatically through the API. The barrier to your first answer is minutes, not weeks.
Request a sample through this page and the team will get you access to a representative cut of the dataset scoped to your market of interest. From sample to live analysis is typically a same-day process. If you want to see the full dataset in the context of your specific candidate sites before committing, book a 30-minute session and we will run it together.