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Geospatial Analytics for Retail Site Selection

Data-driven location intelligence platform for optimal retail store placement and market penetration strategies

28%
Revenue Increase
85%
Success Rate
50%
Analysis Speed

Challenge

A growing retail chain needed to optimize their expansion strategy but lacked sophisticated tools to evaluate potential locations. Their traditional approach relied on basic demographic data and intuition, resulting in inconsistent store performance and missed opportunities in high-potential markets across multiple geographic regions.

Solution

We built a comprehensive geospatial analytics platform that integrated demographic data, foot traffic patterns, competitor analysis, transportation accessibility, and economic indicators. Using machine learning algorithms, the system scored potential locations and provided detailed market penetration analysis with interactive visualization dashboards for decision-makers.

Results

New store locations selected using the platform showed an average 28% higher revenue compared to previous site selection methods. The success rate of new store openings increased to 85%, significantly reducing expansion risks. The automated analysis process reduced location evaluation time by 50%, enabling faster market entry and competitive advantage.

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