E-commerce customer segmentation project using RFM Analysis (Recency, Frequency, Monetary) in R. Features advanced data cleaning, 8+ diagnostic charts, and 2 executive dashboards. Designed to identify high-value segments and provide prescriptive strategies for customer retention and revenue growth.
The E-commerce store had a large customer base but didn't know which customers were "VIPs" and which were about to "Churn."
Data Processing: Used R to clean and transform raw transaction logs.
RFM Modeling:Calculated Recency, Frequency, and Monetary scores to segment customers into 5 groups (e.g., Champions, At-Risk, Loyal).
Visualization: Created 2 interactive dashboards to track segment movement and revenue contribution.
Key Insight (The "Diagnosis"): We found that 20% of the "At-Risk" customers contributed to 40% of the previous year's revenue.
Recommendation (The "Prescription"): I proposed a targeted email campaign with a 15% discount specifically for the "At-Risk" segment to re-engage them.