Placer.ai’s pricing FAQ says a subscriber can analyze an unlimited number of properties, chains and industries. That reach matters most early, when a chain is still choosing a region rather than an address. Only two of the ten tools below publish a price for any plan, so for most of them the first step is a sales call.

Metro, Trade Area or Site: Which Question Comes First

Expansion usually runs through three questions, in this order.

The metro question asks which region or city has room for another unit. The evidence is demand, competitor density and white space, meaning areas where a brand’s likely customers live with no store nearby. The trade-area question narrows that to the part of a metro a store would draw customers from, usually set by drive time or distance. A metro can pass the first test and still have only one or two trade areas worth a store.

Picking the address comes last, and here the evidence gets specific: visits to nearby stores, a revenue forecast, and the risk of cannibalization, where a new unit takes sales from an existing one.

Each entry below opens with the stage it serves best.

1. Placer.ai

Stage: metro to site.

Placer.ai uses mobile-device panels to measure visits at any US property, including a rival’s stores. A team can rank properties by visits, follow audience journeys and compare a candidate trade area with a competitor’s. So a chain can check a new market against the visit patterns at the stores it already runs. Visit trends also show whether a corridor is growing or fading before a chain commits to it. The company says more than 4,000 customers use it. Company-wide licenses and single seats both go through its pricing form, and a free version shows part of the platform.

2. SiteZeus

Stage: metro to site.

SiteZeus runs a white-space analysis that projects revenue potential across the whole country. Its homepage pitches the tool as a way to find where new territories are needed. Once a market is picked, Territory Management draws custom territories inside it and fine-tunes them. At the address level, Locate predicts revenue for any candidate site and uses visitors’ mobile location data to map their paths to purchase. The industries it lists include restaurants, retail, convenience stores, grocery and personal services. Pricing is quote-only, and every sale runs through a demo.

3. Esri ArcGIS Business Analyst

Stage: metro and trade area.

Esri‘s demographic data tool covers more than 170 countries and over 15,000 variables. Its Smart Map Search returns the areas that match a set of criteria, a direct way to turn a long list of metros into a short one. US buyers are sent to a sales team and buyers elsewhere to a distributor.

4. CARTO

Stage: any, built by an analyst.

CARTO lets a team build its own expansion model inside the company’s data warehouse. Its low-code Workflows chain steps such as address geocoding and Create Isolines, which draws travel-time areas around points. The Data Observatory adds paid premium data and public data, such as American Community Survey figures for block groups. Those are the small neighborhood units the Census Bureau reports on. The free 30-day trial includes a CARTO Data Warehouse instance, and pricing is by quote.

5. Gini by MyTraffic (formerly Geoblink)

Stage: metro, mainly in Europe.

AI assistant Gini, from MyTraffic, turns the where-next question into a prompt. One example on its site asks for markets with low competitive density for fast-food restaurants in Germany. Answers draw on MyTraffic’s footfall data, and the company says 600 companies across Europe use it. The Tiny plan costs 249€ a month on monthly billing and covers 1 country, with a free trial. Teams working in more than one country move to a custom tier, which is also where the revenue forecast models are.

6. SiteSeer

Stage: metro to site.

SiteSeer groups its expansion tools on the Advisor plan: White Space analysis, Territory Optimization and Scorecards. To estimate sales for one site, its forecasts combine analog models, machine learning and cannibalization analysis. The platform also includes mobile device foot traffic data. SiteSeer was built by retail industry veterans, and its own page aims Advisor at multi-location retailers and investors. Subscription prices aren’t published, and the Enterprise plan comes with professional services.

7. Tango

Stage: site, for larger chains.

Enterprise real estate software maker Tango ties site selection to the rest of a property portfolio. More than 650 enterprises use it, by the company’s count, and pricing is by quote. Its retail suite uses machine learning to find sites like a chain’s best stores and forecast their sales. Scenario development predicts what a real estate decision will do before the chain makes it. The same system handles lease administration and accounting.

8. Kalibrate

Stage: metro.

Kalibrate says its white-space analysis finds the total unit potential in a region and the best places to put those units. Cannibalization thresholds manage how much sales transfer between sister stores. Excel data can be dragged into the software and geocoded automatically, and a native iOS and Android app supports site tours. Pricing is quote-only and depends on licensed data, seats and analytics. Kalibrate goes deepest in fuel and convenience retail, where it also sells fuel pricing software.

9. GapMaps

Stage: metro and trade area, especially in data-poor markets.

Australian location data company GapMaps builds its own population data, modeled from billions of mobile device location points down to a 100-meter grid. That approach helps where census data is thin, and its customer stories include Nando’s in Malaysia and Eat’n’Go in Nigeria. Catchments, its word for trade areas, can be set by drive or walk time, time of day and day of week. GapMaps claims coverage across 25 countries, but its site does not describe US data depth.

10. Maptive

Stage: trade area.

Maptive works from a chain’s own customer and sales file. Find Market Gaps colors ZIP codes by a brand’s best-customer profile, surfacing lookalike areas no store covers yet. A Compare Two Markets view puts a pair of candidates next to each other. Its built-in census data goes from the state level down to the block group, but it covers only the US and Canada. In the European markets Gini serves, a Maptive map can be shaded only by the user’s own numbers.

Where a Smaller Operator Can Stop

A chain with a few dozen units rarely needs to license outside visit or forecast data for the first two stages. Its own customer file already shows where its buyers live. Esri’s Business Analyst and Maptive’s location intelligence tools both set that file against census data, at different depths. Either can usually narrow the metro list and outline a trade area without a data contract.

The site stage is different. Observed visits at a rival’s store, a revenue forecast for one address and an estimate of sales transfer are the evidence a lender or franchise committee usually asks for, and they come from vendors with their own data.

For a chain opening two or three units a year, the practical order is to screen with what it owns, then buy the site-level evidence for the few addresses that survive.

Photo: RDNE Stock project via Pexels

CLICK HERE TO DONATE IN SUPPORT OF OUR NONPROFIT COVERAGE OF ARTS AND CULTURE