Top 10 tools to compare store locations in 2026

Ten tools show up again and again when retail teams compare candidate store locations.

Picking the wrong tool for that question wastes weeks or even months, but might still be a better decision than not having a tool at all. The Centre for Retail Research counted around 14,000 UK store closures in 2025, with roughly 150,000 retail jobs lost, and expects a similar number in 2026. I believe that a big part of these closures aren't based on just poor management or policy, but poor location decisions.

The three questions, and why they decide the tool

Every tool on this list answers one of three questions well, and usually only one:

1. Who goes there? Observed footfall. Real visit counts, visit frequency, where visitors came from beforehand.
2. Is there room for us? Market potential. Catchment size, demographics, spend, competitive density, available leases.
3. Which site is the best, and what will it turn over? A decision-ready comparison, ideally with a revenue number attached to each candidate.

That third question is the one a real estate committee asks, and it's the one most tools on this list won't answer for you.

Below is an honest ranking of the ten tools retail expansion teams often put in their shortlist. Each entry names which question it answers, what it costs, and where it stops.

The ten tools at a glance

1. Gini by MyTraffic

Gini by MyTraffic is built for the fullsite selection process. You ask a question in plain language, and the AI companion pulls GPS mobility data, footfall counts, catchment demographics and market potential into a direct answer. Unlike the other tools on this list, Gini answers all three questions from one query instead of specialising in one of them, which is the difference between a shortlist ranked in an hour and a .xls file with 15 different dashboards cross referenced over a full week.

On top of it's speed, Gini by Mytraffic acts more like a site selection consultant, giving you real actionnable answers, avalaible in 18 markets across Europe and the US, so a retailer scoring a site in Lyon and one in Rotterdam gets the same measurement standard and quality on both.

Two constraints are worth knowing before you buy:

• Coverage stops at those 18 markets, so a retailer expanding into a nineteenth, Czechia or Greece or anywhere outside Europe and the US, isn't served.
• The entry plan covers one country of your choice and five analyses a month, which suits a franchisee or a solo analyst but not a team screening across borders; multi-market coverage and revenue forecasting both sit on the Plus tier.

The Tiny plan is €249 a month with a free trial; while the Plus plan, which unlocks all 18 markets and revenue forecasting, is custom-priced

This tool is really made for etail rexpansion teams building and expansion strategy and comparing multiple candidate sites across one or several European countries who want a direct answer, not a GIS project needing a full time data scientist.

2. Placer.ai

Placer.ai reads foot traffic from mobile location data, and its visit-frequency and cross-visitation numbers are strong for understanding how people already use a location. If a site has been open for any length of time, or a nearby comparable has, Placer.ai will tell you who's walking in, how often, and where they came from beforehand.

Placer.ai launched in 2018 on the US market and only began international rollout in 2024, with the UK and Canada first and wider European markets targeted afterwards. It also stops short of ranking your candidates or attaching a revenue number to them, so teams tend to run it alongside a scoring tool rather than instead of one.

I recommend Placer.ai for teams that need deep, US-weighted visit and cross-visitation data and can absorb an enterprise sales process to get it.

3. Esri ArcGIS Business Analyst

Esri is the GIS industry's default: demographic layers, drive-time modelling and trade-area mapping go deeper here than almost anywhere else on this list, across more than 170 countries. If your team already runs GIS workflows elsewhere in the business, you might already have this tool in your stack.

The trade-off is who can actually use it. ArcGIS assumes a GIS analyst on staff, or at minimum someone comfortable building spatial models rather than typing a question into a search bar. It is not built for a run of the mill expansion director with a managemental profile. It models market potential from demographic data; it won't tell you who actually visits a site, and it won't hand you a sales forecast.

I recommend Esri ArcGIS for organisations with an in-house GIS team who want maximum control over how the spatial model is built.

4. SiteZeus

SiteZeus is built for the franchise and multi-unit world. If you're opening the fortieth unit of a format and want a model tuned on how the first thirty-nine performed, this is a purpose-built option. Its sales projection, the Zeustimate, drops a revenue number on any pin and re-calculates it when you change site attributes like square footage or drive-thru count, which is exactly the output a committee asks for. SiteZeus also relaunched as a conversational platform called Atlas in May 2026.

Where it asks more of you is scale and data. The model learns from your existing fleet, so a five-store regional retailer gets far less out of it than a 300-unit QSR brand, simply because there isn't enough performance history to train on. Its data coverage is also US-centred.

5. Buxton

Buxton starts on the customer side rather than the site side. It profiles who your best existing customers are, then finds more of them elsewhere. For a retailer whose expansion strategy starts with "we know who buys from us, so where else do they live?", that's a different starting point from a foot-traffic or GIS tool. Buy the forecasting version of the site score model and it will project revenue and cannibalisation for a candidate site too.

It does have a small limit though: it needs an established customer base worth analysing, so it's a poor fit for a young brand or if you have a poor data collection system.

Buxton is ideal for established retail brands leading expansion with a customer-segmentation lens. Other tools on this list can do it too, but Buxton is specialized in this.

6. Kalibrate

Kalibrate builds sales forecasting models calibrated to a specific brand, combining mobility data, demographics, competitive location data and trade-area definition into a projected revenue figure per site. It has decades of work in fuel, grocery and quick-service restaurants, and unlike most of the forecasting tools here it has run multi-country European deployments, including whitespace analysis across several markets at once.

The trade-off is that the model is analyst-mediated rather than self-serve. You engage Kalibrate, they build and calibrate the model, and you get a defensible number. That's the right model when you have a €2m fit-out hangs on the forecast, but is limited for smaller operations or moments when you need a quick answer. If you can afford to wait some time for an analyst's answer, Kalibrate is a great option for site selection.

7. CARTO

CARTO is a geospatial analytics platform built for teams who want to write their own models rather than accept someone else's scoring logic. It's popular with analysts working in Python or SQL who treat location data as infrastructure: pull in your own footfall exports, join them against CARTO's spatial layers, ship a custom dashboard.

That flexibility is the appeal and the limitation at once. Without a data science function, CARTO asks for real setup work before it returns a usable answer, closer to engineering than a quick check on a lease you've been sent. It fits as the engine behind a custom internal tool, not as something a store development manager opens to compare two addresses next week.

I would recommend Carto to analyst-led teams building custom location models in-house.

8. Smappen

Smappen is the fast first pass. Drawing a drive-time or walk-time catchment and overlaying basic demographics takes minutes, not a training session, and its customer base skews heavily towards small businesses and franchise development teams for exactly that reason. For a franchisor scoring a handful of candidate units a quarter, it's often enough to take decisions.

What Smappen tells you is who lives in the zone, not who actually visits it. It runs on static demographic and geographic data rather than observed movement, so two sites with identical catchments on paper can perform completely differently once open, and Smappen alone won't show you why. Verify the finalists against observed footfall before signing.

If you're a small network or a franchisee who need fast, low-friction catchment definition before deeper diligence, then Smappen is a great tool for you.

9. Google Earth

Google Earth isn't a site-selection platform and was never built as one, but real estate teams use it constantly as a free sanity check. Measuring visibility from the road, checking what's next door, or confirming parking access before a site visit are jobs Google Earth still does better than most paid platforms bother to do.

It answers none of the three questions on its own. It won't rank your candidates, forecast revenue, or tell you anything about who visits a location. But it will save you time visiting poor sites with just a quick check. Treat it as a support tool running alongside whichever platform is doing the comparison.

10. Tableau

Tableau doesn't collect location data. It turns whatever store, market and footfall data you already hold into dashboards your team and your real estate committee can read. If your problem is less "we lack data" and more "we have data in six spreadsheets and no one agrees on what it shows", Tableau is where that gets solved.

That also makes it the wrong tool to reach for first. Feed it clean, comparable site data from one of the platforms above and it!

The bottom line

Of the ten tools above, one answers the footfall question precisely (Placer.ai), three answer market potential from modelled or static data (Esri, CARTO, Smappen), three build a decision-ready comparison with a revenue forecast attached (SiteZeus, Buxton, Kalibrate), and two exist purely to support whichever tool is doing the real analysis (Google Earth, Tableau).

Gini by MyTraffic is the one entry that answers all three itself, and it does so across 18 markets on a single measurement standard. That's the whole argument for putting it at the top of a comparison list, and it's also why the constraints above matter: if your expansion is confined to one country and you never need a revenue model, the entry plan is enough, and several tools further down this list will do that one job well.

If you're comparing two or three candidate sites right now and want to see how they stack up on observed footfall rather than catchment guesswork, that's the question Gini is built to answer. Bring it your current shortlist and see the ranking.