MENA Coffee Chain: Site Selection in Days, Not Weeks

The chain's growth strategy depended on opening 30+ stores per year across the Gulf, but site selection was the bottleneck. Each candidate site required weeks of manual analysis: demographics from one consultancy, footfall from another, competitor mapping done by hand. New stores opened 8 months after the property team first identified a site.

Worse, the analysis frequently missed the patterns that mattered. Two stores in seemingly identical demographics could differ by 40% in revenue, and the team couldn't explain why.

The team deployed Amakin to score every candidate site against a consistent set of spatial signals: catchment population, time-of-day footfall, competitor density within 200m, distance to nearest metro exit, and accessibility on foot vs. car.

What used to require three external vendors and six weeks of work became a single dashboard rendered in minutes. The team trained the predictive model on their existing 200 stores, so the score for new candidates was calibrated against actual revenue, not generic benchmarks.

Within six months the chain's new-store performance moved meaningfully. Sites scoring above the model's 75th percentile hit projected revenue within three months — versus the 60% accuracy rate the old process delivered. The property team now reviews 4x more candidates with the same headcount.