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Customer Analytics
CRM Optimization via RFM Segmentation
Customer behavior analysis at AI² Mart Jakarta using RFM Segmentation (Recency, Frequency, Monetary) and Coefficient of Variation (CV) to identify purchasing pattern consistency. The results are used as a basis for more targeted marketing strategies.
Detailed Insights
RFM & Segments
Customers classified into 11 segments. Hibernating and Lost dominate the database. Valuable segments like Champions and Loyal Customers require specific retention campaigns.
Coefficient of Variation (CV)
Used to measure customer transaction stability. More than 80% of critical customers were dominated by the Uncertain category, meaning the business needs data enrichment.
Campaign Strategy
Dual approach untuk Champion (upsell + cross-sell), win-back campaign untuk At Risk, serta re-engagement incentive untuk segmen Hibernating.
Tech Stack
PythonPandasRFM ScoringCV Analysis
Key Results
- 131,706 transactions from 22,129 customers
- 11 RFM segments identified
- Hibernating (33.8%) & Lost (25.1%) dominance