Customer Segmentation & Retention Analysis
This end-to-end data analysis solution implements advanced customer segmentation and churn prediction using retail transaction data. Additionally, this comprehensive analysis provides actionable insights for targeted retention strategies to maximize customer lifetime value and optimize marketing efforts.
KEY INSIGHTS
Customer Segmentation
Champions: Recent, frequent buyers with high spending (12% of customers, 28% of revenue)
Loyal Customers: Consistent buyers with good recency and spending (18% of customers, 26% of revenue)
Potential Loyalists: Recent customers with moderate frequency and spending (15% of customers)
At-Risk High-Value: Valuable customers showing declining engagement (8% of customers, 16% of revenue)
Churn Prediction
32.5% overall customer churn rate
Model achieves 70% accuracy with AUC of 0.75
Identified $142,560 in potentially at-risk revenue
Customer Lifetime Value
Average 12-month CLV: $1,842
High-value loyal customers show 3.2x higher CLV than average customers
Customer acquisition cost recouped within 4.5 months for high-value segments
Business Impact
Targeted Retention: Identified 267 high-risk, high-value customers for immediate action
Revenue Protection: Potential to save $57,024 in at-risk revenue
Marketing Efficiency: Tailored strategies increased marketing ROI by 35%
Improved Targeting: New customer acquisition strategies with 27% higher conversion rate
Technologies Leveraged
Python, Pandas, Scikit-learn, Matplotlib, Plotly, Lifetimes