Advanced Customer Segmentation

Overview

This project focuses on developing advanced clustering techniques to improve customer segmentation in financial services. By optimizing for profit separation rather than traditional distance metrics, we achieved significantly better business outcomes.

Key Achievements

• • Developed custom clustering algorithms optimized for profitability
• • Improved customer targeting accuracy for marketing campaigns
• • Implemented scalable solutions for millions of customer records
• • Enhanced predictive models through better feature engineering

Approach

The methodology combines traditional clustering techniques with business-driven optimization objectives. This ensures that segments are not only statistically distinct but also actionable from a business perspective.

Technologies Used