Overview
This project focuses on segmenting customers based on their purchasing behavior using Recency, Frequency, and Monetary (RFM) analysis. The goal is to identify meaningful customer groups that can support data-driven marketing and retention strategies.
What I Built
- RFM feature engineering to quantify customer purchasing behavior
- Customer segmentation using clustering techniques
- Evaluation of cluster quality to ensure meaningful and well-separated segments
- Interpretation of customer segments for actionable business insights
Tools & Technologies
- Python – data preprocessing and analysis
- Pandas & NumPy – feature engineering and data manipulation
- Scikit-learn – clustering and evaluation metrics
- Matplotlib & Seaborn – data visualization and cluster analysis