RFM Customer Segmentation for E-commerce

RFM Customer Segmentation for E-commerce Retention Analysis Built a customer segmentation model using RFM (Recency, Frequency, Monetary) analysis to identify high-value customers, at-risk users, and churned segments.

The dataset was structured from order-level e-commerce transaction data and processed to generate actionable customer-level insights.

Key work included:

Calculating Recency, Frequency, and Monetary values per customer

Scoring customers using percentile-based ranking and NTILE logic (SQL validation)

Segmenting customers into actionable groups:

Cross-validating segmentation logic between Excel (Power Query) and SQL (PostgreSQL)

Structuring outputs for CRM and retention strategy use cases

Final output: fully segmented customer dataset ready for marketing targeting and retention campaigns.

This project demonstrates applied customer analytics for e-commerce growth and retention optimization.