2020 USA Demographics, Housing and Business Data with Projections

Plan every location before you commit the capital

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.

Isometric white geographic platform with blue trade areas, routes, markers, partitions, and floating data cards representing portfolio-scale demographic analysis.
At a Glance

The Data Behind the Decision

Block Group
Finest geographic unit available
Age, Sex & Race
Full demographic dimension coverage
Base + Projected
Current and forward-looking coverage
Buy by Geography

Stop buying the whole country. Buy just your markets.

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.

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See It Run Across Your Footprint

The Problem

Your Portfolio Decisions Deserve Better Data

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.

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Fragmented Demographic Data Sources
When GIS, store ops, and strategy all pull from different demographic sources, your models never agree. Capital decisions get made on the loudest spreadsheet in the room, not the most accurate data.
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Cannibalization Caught Too Late
Without block-group precision across your full footprint, overlapping trade areas stay invisible until comp sales decline. By then, the cannibalization has already happened and a new lease is already signed.
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Format Targeting Without Demographic Proof
Testing a smaller format or a value-tier concept in a new market requires knowing who actually lives in the catchment, not who lived there in the last census cycle. Stale data produces confident wrong answers.
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Projection Gaps in Multi-Year Planning
Real estate decisions have five-to-ten-year time horizons. Planning against static demographic snapshots means your site model is aging out before the lease even opens.
What Is In The Dataset

One Demographic Layer for Your Entire Portfolio

Block-Group Geographic Precision

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.

Age and Sex Segmentation

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.

Race and Ethnicity Dimensions

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.

Forward Demographic Projections

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.

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The world's spatial data is more accessible than you think. Let's show you how close you already are.
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You already have the questions. We have the data. Let's see what happens when they meet.
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The where in your business is more important than you think. Let's find it together.
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Most spatial data conversations start with a problem nobody thought was solvable. What is yours?
BigGeo AI

Ask Any Portfolio Question in Plain Language and Get a Governed Answer

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.

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Which of our top 50 stores have a 5-mile catchment where the 25-44 age cohort is projected to grow by more than 10% by 2028?
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Show me all block groups within 3 miles of our proposed Houston site where median age is under 35 and Hispanic population exceeds 40%.
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Which existing stores share more than 30% of their block-group catchment with a proposed new location in the same DMA?
FAQ

Frequently asked questions

We already have demographic data from another vendor. Why would we replace it with this?
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How does block-group data actually change a cannibalization model compared to ZIP-code or tract-level data?
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How current is this data and how far out do the projections run?
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Can our GIS team query this directly without going through BigGeo's interface?
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What does getting started actually look like for an enterprise team?
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