How to choose a business location: a practical, evidence-first method

The method, step by step

Eight steps from “somewhere around here” to a defensible shortlist

Run the steps in order. Each one eliminates candidates cheaply before the expensive checks — visits, negotiations, buildout quotes — begin. The worked logic is the same whether you are opening one shop or screening a pipeline with bulk analysis.

1. Define the target customer — before touring any property. Write down who the business serves: age band, income band, household type, habits (walk-in vs. planned visit, day vs. evening). Touring first and rationalizing later produces a shortlist shaped by what happens to be vacant, not by what the business needs. If you already operate elsewhere, plot where current customers come from and treat that profile as the template.
2. Screen the geographic market. Narrow to a few districts where that customer plausibly concentrates. Use population grids and, where you have them, your own customer origins — not ZIP-code averages alone, which hide the street-level variation that decides a site. This is the market-screening stage of business expansion analysis.
3. Measure demand around each candidate. For every candidate address, count the population within a realistic radius — 1, 3 and 5 miles (or 1, 3, 5 km) is the standard first cut — from gridded demographic data. Ask what share of that population plausibly buys what you sell: a 40,000-person catchment means little if your category serves 4% of it. Daytime population matters for lunch and convenience formats; residents who commute away all day are a smaller market than the headcount suggests. Read the full workflow in business location analysis.
4. Map competitors — and saturation, not just counts. List same-category businesses inside the radius with distance and strength signals (ratings, reviews, price level). A street with dozens of fashion units is hostile to another fashion unit and wide open to a category the street does not serve. Saturation is always category-specific. The technique is competitor analysis; the inverse question — which categories are missing — is answered by white-space analysis.
5. Delimit the real trade area. A radius ring is fast and good enough to disqualify candidates, but it ignores roads, rivers and traffic. For the shortlist, replace rings with drive-time: what can actually reach the site in 10, 20 or 30 minutes along the road network. Two sites with identical radii routinely have very different drive-time catchments, and the drive-time picture is the one customers actually drive. See trade area analysis.
6. Check accessibility and complements. Verify ingress and egress, parking at peak hours, visibility from the dominant approach, and transit context. Then check co-location: which anchor categories share the area and send customers your way — the complementary mix described under location intelligence. A strong trade area with a site customers cannot enter easily still underperforms.
7. Compare candidates side by side, same inputs. Score at least two or three candidates on the same date, for the same business category, with the same radii: population, competitor density, access, complements, rent. Set the weights before scoring, apply them identically, and read where candidates diverge field by field. The discipline matters more than the weights — and restaurant location analysis shows how the same address scores differently per category, and coffee shop location analysis does the same for a single-format business.
8. Validate before signing. Visit finalists at the hours you will actually operate, confirm zoning permits your use in writing (a binary gate — nothing compensates for a blocked use), compare total occupancy cost against your margins, and treat thin or empty data as no coverage, not zero. Then decide: the evidence narrows the choice, the business judgment closes it.

An honest limitation, stated up front

No score will choose for you — and that is deliberate

Many site tools compress everything into a single grade computed by a model you cannot inspect. When that number moves your lease decision, you cannot ask what it assumed, which inputs it weighted, or how current its data was.

LocateRight takes the opposite stance: it hands you the measurements the way a surveyor hands you readings — competitor counts with listings behind them, population with the grid and vintage named, coverage gaps labeled as gaps. Whether a site is right is a business judgment depending on your margins, format and strategy, and the software does not pretend to own it. The platform says so in its own footer: it does not produce scores, rankings or recommendations.

If you use new categories for the first time, the usage guide explains what each block means and the about & data sources page inventories every provider.