The Problem
Retailers struggle with product placement optimization and identifying which items should be bundled, discounted together, or positioned strategically. Manual analysis is slow and inaccurate.
Data & AI
Market Basket Analysis
A data-driven insights platform for grocery and retail stores, helping them understand which products sell together and how placement affects overall sales performance. The system uses Market Basket Analysis (MBA) techniques to generate meaningful association rules.
Problem and Solution
Our Solution
An AI-powered MBA engine that analyzes large volumes of purchase data and provides actionable insights for: Product placement, Bundle recommendations, Seasonal demand patterns, Cross-sell opportunities, Inventory optimization.
Features
Key Features
Support, confidence, lift analysis
Association rule mining
Visual dashboards for product relationships
Store-level and category-level insights
Predictive customer behavior models
Placement recommendations for commercial aisles
Stack
Technology Stack
Python (ML models)Node.js APINext.js frontendPostgreSQLRecharts for visualization
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