Trade area analysis: how to define the geography that actually buys from you

Trade area analysis is the first step of any credible site selection decision. Everything downstream — demand estimates, competitor counts, sales forecasts — inherits the boundary you draw. Draw it badly and every number after it is wrong in the same direction.

What a trade area is

A trade area is the geography from which a location draws the large majority of its customers. In practice teams model a primary trade area (roughly 60–70% of visits), a secondary ring (another 20%), and a tertiary tail that is real but not worth planning around.

Drive time beats radius

A three-mile radius assumes customers travel as the crow flies. They do not. Rivers, motorways, rail lines, one-way systems and tolls all distort reach. A ten-minute drive-time isochrone around a suburban unit can cover four times the population of a ten-minute isochrone in dense urban core, and both are more honest than a circle.

What to measure inside it

• Resident population and household count, from the US Census American Community Survey or Statistics Canada census profiles.
• Income and age mix, weighted toward the bands that buy your category rather than the overall median.
• Daytime population, which matters more than residents for lunch-led and service formats.
• Competitive supply, counted as comparable operators inside the same boundary — not inside a wider region.
• Accessibility friction: parking, transit stops, turn-in visibility.

Validating the boundary

If you already operate stores, your own transaction data is the best trade-area calibration available. Geocode customer postcodes, plot them, and find the isochrone that captures 65% of them. That empirical shape, applied to comparable formats, beats any default ring.

Common mistakes

Three failures repeat: using one radius across every market regardless of density; counting competitors in a wider area than demand; and treating the trade area as static when a new competitor opening reshapes it within a quarter. Re-run the analysis on a schedule, not once per lease.

Doing it faster

Georithm assembles the isochrone, live census demographics, OpenStreetMap competitor counts and climate context from a plain-English question, then shows the per-factor contributions behind the score so you can argue with the inputs rather than trust a black box.