AI-Tool for selecting locations for retail roll-out for a optical precision lens producer

Client:

Market-Leading Prescription Lens Manufacturer

Challenge:

The client needed to optimize their retail footprint by identifying the highest-potential locations for existing and new stores for a product rollout with very high-capex, and a strong focus on maximizing sales for key product categories.

Approach:

• Developed an AI-driven analytics tool that integrated multiple data sources including demographic information, consumer behavior patterns, competitor locations, and historical sales data
• Created a sophisticated ranking algorithm that evaluated locations based on projected sales potential
• Built a predictive model to forecast sales volumes for specific product lines at each potential location
• Built a predictive model to forecast ROI of device installation
• Designed an intuitive interface for Head of distribution and sales teams allowing business users to visualize location data and run scenarios

Results:

• Adapted by the client for providing actionable intelligence for the client’s retail expansion strategy
• Created a prioritized ranking of existing store locations for specific product focus
• Identified several high-potential locations that had been overlooked by conventional analysis
• Generated precise sales volume predictions that exceeded traditional forecasting accuracy
• Tool continued to improve over time through machine learning from actual performance data