The USA Demographics, Housing and Business Data with Projections from Applied Geographic Solutions delivers block-group-level population, age, sex, and race data with forward projections across every market in your portfolio. For the first time, your GIS, store operations, and corporate strategy teams work from a single governed demographic layer that runs at the scale of your entire footprint.

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.

Enterprise retailers and real estate portfolios carry the weight of hundreds of capital decisions made on demographic assumptions that were stitched together from different sources, at different times, in different formats. The result is not a unified view of the market. It is a patchwork that makes cannibalization invisible until it shows up in comp sales.
Block-group resolution means you can draw a trade area around any existing or proposed location and know exactly who lives inside it, down to the sub-neighborhood level. That precision is what separates a real cannibalization model from a rough overlap estimate.

Every block group carries full age and sex breakdowns, letting your format planning team validate whether a proposed concept actually matches the demographic composition of its catchment before a single dollar of capex is committed.

Demographic targeting models built without race and ethnicity data miss the most predictive signals in consumer behavior by market. This dimension lets your strategy team test and validate targeting assumptions at the block-group level across your full portfolio.

Projected population data alongside base gives your real estate committee a forward view of catchment growth, decline, or composition shift, so your site model reflects who will be in the trade area when the lease matures, not who was there when it was signed.

BigGeo AI is live in ChatGPT today and shipping in Claude, giving your analysts direct access to this demographic dataset through plain-language questions, no GIS software required. A store planning analyst can now ask a demographic catchment question across your entire portfolio in seconds and get an answer grounded in the Applied Geographic Solutions data, governed by your access configuration, without waiting for a GIS pull or a data team ticket.
The question is not whether you have demographic data. The question is whether every team in your organization is working from the same version of it at the same time. When GIS runs a separate pull from strategy and store ops runs a third, your models diverge before anyone gets to the answer. BigGeo puts this dataset in a single governed layer so every query, regardless of team, returns the same number from the same source.
ZIP codes and census tracts are large enough to hide the overlap that matters. Two stores can appear to serve distinct trade areas at the ZIP level while sharing 40% of the same block groups. Block-group resolution exposes that overlap before it becomes a comp sales problem. At enterprise scale, that difference in precision changes which sites get approved and which do not.
The dataset is anchored to the 2020 decennial census base, which is the most thorough block-group enumeration available in the USA. Applied Geographic Solutions builds projections forward from that base using validated demographic models, giving your planning team a view that extends beyond the current period into the multi-year horizon your real estate decisions actually require. Coverage and projection horizon details are available when you request a sample.
Yes. Data purchased through BigGeo lives in your DataLab workspace, where it can be queried through standard spatial workflows or accessed programmatically by your GIS team. The compute engine runs server-side, so your analysts are not waiting on data exports or local processing. Enterprise licensing is specifically structured to support concurrent access across GIS, store operations, and corporate strategy.
Request a sample and your team gets access to the dataset for a defined set of locations so you can validate it against your existing models before any enterprise commitment. Most teams who run that comparison come back with a list of discrepancies that justify the switch on their own. A 30-minute call with our team covers how enterprise licensing is structured and what a full portfolio deployment looks like in practice.