Site selection, built on facts you can trace

Why one number is never enough

Good site selection weighs several independent signals

A location decision fails most often not for lack of data but for lack of cross-checking. A neighborhood with strong footfall can still be saturated with direct competitors; a quiet parcel can sit inside a dense residential catchment that never shows up in a simple drive-by. Before committing rent, most teams want the same set of questions answered around each candidate:

LocateRight keeps all four signals on one canvas: the map for spatial judgment, an evidence sheet of counts and listings for scrutiny, and provenance labels underneath everything.

How the workflow runs

From address to decision sheet in one session

1. Fix the candidate. Search a place, paste coordinates or drop a pin — optionally set a draft location you are considering before it exists on any map. Choose a business category and a radius, or draw the area itself.
2. Read the dossier. The analysis assembles places and category density, competitor listings, population within the radius and the nearest-city context. Each block states its provider and retrieval date; thin coverage is flagged, not filled in.
3. Deepen selectively. Run the metered tools only where a site still stands: White Space for underserved categories, Co-location for anchor mix, Accessibility for drive-time reach.
4. Compare side by side. Put two or three shortlisted sites next to each other and read the per-field deltas — counts and densities, no verdict attached. For a longer pipeline, bulk analysis takes a CSV of addresses and returns one table of site metrics with export.

Positioning, stated plainly

Raw evidence instead of a proprietary score

Most site selection tools compress everything into one number — a “grade” or “score” computed by a model you cannot inspect. That convenience is also the risk: when a score changes your lease decision, you cannot ask it what it assumed, which inputs it weighted, or how current its data was.

LocateRight takes the opposite stance. It is a location intelligence platform that hands you the measurements the way a surveyor hands you readings: competitor counts with their listings behind them, population with the grid and vintage named, coverage gaps labeled as gaps. Whether a site is right is a business judgment that depends on your margins, format and strategy — the software should not pretend to own it.

Making the call

A practical way to turn the evidence into a decision

Because LocateRight does not rank sites for you, here is the discipline that works in practice — four checks any candidate should pass before it reaches your shortlist:

• Demand check: is there population within your realistic radius — and does the draw-time view of it match how customers actually reach you?
• Supply check: how many same-category competitors are already inside that radius, and how do their ratings and price levels look?
• Context check: do the anchor categories you assumed are nearby actually exist? Co-location turns assumptions into counts.
• Coverage check: before trusting a thin or empty block, confirm whether the underlying dataset covers the region at all — the label tells you, instead of a zero lying by omission.

When two candidates still disagree on a field, run the compare view and inspect the per-field deltas next to the two dossiers. For the full step-by-step method this decision sits inside, see how to choose a business location. If you use new categories for the first time, the usage guide explains what each block means and which data sources feed it.