RFM Customer Segmentation for E-commerce

★ 7.2 · general

rfm-customer-segmentation is a Claude Code skill that performs RFM (Recency, Frequency, Monetary) analysis on e-commerce transaction data, automatically cleaning records by removing orders with negative quantities or zero prices, computing per-customer RFM metrics, and applying K-means clustering with the elbow method to determine the optimal number of segments. Each customer receives a 1–3 score on every RFM dimension, producing High, Medium, and Low value tiers along with a ranked VIP list ready for targeted campaigns. Outputs include a PNG analytics dashboard with pie charts, scatter plots, and box plots, plus three CSV files — full segmentation data, a ranked VIP customer list, and segment summary statistics — alongside a plain-text data validation report. Built-in Chinese font and field-name support (用户码, 消费日期, etc.) makes the skill well-suited for analyzing audiences from Chinese marketplaces or any e-commerce dataset where customer lifetime value segmentation and marketing prioritization are needed.