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Use Case 08 · Retail & FMCG

Micro-Location Foot-Traffic & Store Site Selection Engine

Geo-spatial H3 grid scoring for physical store location scouting.

Head of Real Estate Chief Expansion Officer
Illustration: Micro-Location Foot-Traffic & Store Site Selection Engine

Customer need & pain point

The problem this replaces.

  • Multimillion-dollar multi-year lease commitments made on outdated demographic data.

Step-by-step execution

How the engine executes it.

01

Geo-Spatial Intelligence

Module 2

Overlay OpenStreetMap POIs, municipal transport density, and mobility trends onto H3 spatial grids.

02

Spatial Analytics

Module 1 & 2

Analyze nearby competitor density and historical sales performance of existing branches.

03

Multi-LLM Routing

Module 1 & 2

Generate predictive revenue yield estimates per candidate location.

04

Agentic Action

Module 4

Issue executive site-selection dossiers directly to investment committees.

Quantifiable ROI & impact

What changes commercially.

  • 32% improvement in new store opening profitability
  • 75% faster feasibility analysis.

The “aha” moment

“Site selection went from 3 months of manual surveying to a 10-minute spatial AI generation model.”
Global Expansion Director (QSR Chain)