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

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.

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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