End-to-end data analytics project on Customer RFM Segmentation and CLV modeling using SQL, Python ETL, and Power BI insights.
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Updated
Jan 10, 2026 - Jupyter Notebook
End-to-end data analytics project on Customer RFM Segmentation and CLV modeling using SQL, Python ETL, and Power BI insights.
RFM-based customer segmentation analysis for an e-commerce dataset. Includes data cleaning, exploratory analysis, Recency-Frequency-Monetary scoring, segment classification, visual dashboards, and strategic business insights. Designed to identify high-value customers and guide targeted marketing actions
Customer Behavior Analysis
Customer segmentation project using RFM analysis to classify customers based on recency, frequency, and monetary value. This notebook cleans transactional data, calculates RFM scores, assigns customer segments, and visualizes behavior patterns to support targeted marketing and retention strategies.
RFM-based customer segmentation and value analysis using real retail transaction data.
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