Customer Segmentation Analysis

Overview

Created a customer segmentation model for an e-commerce company to identify distinct customer groups and optimize marketing strategies.

Methodology

Applied K-means clustering algorithm on customer purchase history and demographic data. Used PCA for dimensionality reduction and visualization.

Key Findings

• Identified 5 distinct customer segments with unique purchasing behaviors
• High-value customers represented only 15% of the customer base but generated 60% of revenue
• Seasonal purchasing patterns varied significantly between segments

Data Visualization