Score every candidate site on a clear GO / BORDERLINE / NO GO basis — built from your own store history, with revenue estimates and reasoning your team can act on.

Success probability, revenue estimate, and rent viability combined into one authoritative recommendation for every candidate site.
Models trained on your existing outlets and their real performance, not a generic industry template.
Every market gets its own calibration — what works in one city often fails in another for entirely different reasons.
Predicted monthly revenue and rent-ratio analysis, so a site's business case is clear before you negotiate lease terms.
Plain-language reasoning and a specific checklist your real estate team can use on the ground.
Every recommendation is visualized on an interactive map your team can explore, not just a spreadsheet.
For a pan-India retail chain's next expansion round, we scored every candidate site on spatial character, predicted revenue, and rent viability — replacing a process that had relied on individual judgment calls with a consistent, repeatable framework.

One proposed location scored strongest in its entire batch on physical and locational character, but was initially flagged borderline on revenue alone. We flagged it for a field visit instead of an automatic rejection — the kind of judgment a pure spreadsheet score misses.

Find every retailer, dealer, and distributor for your product
View solutionKnow if a market is worth entering, and what your network is telling you
View solutionStreet-level maps of rent, income, and household density
View solutionWe'll tell you what the data can say about it — and whether we're the right fit.