This project demonstrates how clustering techniques can uncover meaningful customer segments using the RFM (Recency, Frequency, Monetary) framework. By transforming raw transaction data into actionable behavioral profiles, we enable smarter marketing, retention, and resource allocation strategies.
- RFM metrics offer a compact, interpretable summary of customer value.
- K-Means clustering revealed distinct behavioral segments, from high-value loyalists to low-engagement buyers.
- PCA visualization confirmed clear separation between segments, supporting strategic decision-making.
- Radar and bar charts highlighted segment-specific traits, enabling tailored outreach and product positioning.
This segmentation model empowers businesses to:
- Personalize campaigns based on customer behavior
- Prioritize retention efforts for high-value segments
- Design differentiated experiences that drive loyalty and lifetime value