This project applies RFM (Recency, Frequency, Monetary) analysis to segment customers based on their purchasing behavior and business value. Using SQL for data processing and Power BI for visualization, the project helps identify high-value customers, churn risks, and customer engagement opportunities.
The analysis focuses on identifying:
- High-value customers
- Loyal and repeat customers
- Customers at risk of churn
- Inactive customer segments
- Opportunities for customer retention and engagement
- SQL
- Power BI
- Customer Analytics
- RFM Analysis
- Identified Champions and Loyal VIP customers contributing significantly to business value
- Detected At Risk and Lost customers requiring retention strategies
- Segmented customers based on Recency, Frequency, and Monetary metrics
- Revealed customer behavior patterns to support targeted marketing efforts
- Customer Segment Distribution
- RFM Score Analysis
- Customer Retention Insights
- Loyalty & Churn Analysis
- Interactive Filters & Visualizations
- Raw Datasets
- SQL Analysis Queries
- Power BI Dashboard (.pbix)
- Dashboard Screenshots
- Project Documentation
- Cleaned Dataset
Refer to the detailed project documentation for complete methodology, RFM scoring logic, customer segmentation process, business insights, and dashboard explanation.