• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models. • Built Decision Tree and Random Forest models for churn prediction. • Integrated survival probabilities into Customer Lifetime Value (LTV) estimation. • Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.
2024
• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models.
• Built Decision Tree and Random Forest models for churn prediction.
• Integrated survival probabilities into Customer Lifetime Value (LTV) estimation.
• Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.
• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models. • Built Decision Tree and Random Forest models for churn prediction. • Integrated survival probabilities into Customer Lifetime Value (LTV) estimation. • Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.
2024
• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models.
• Built Decision Tree and Random Forest models for churn prediction.
• Integrated survival probabilities into Customer Lifetime Value (LTV) estimation.
• Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.
• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models. • Built Decision Tree and Random Forest models for churn prediction. • Integrated survival probabilities into Customer Lifetime Value (LTV) estimation. • Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.
2024
• Analyzed customer churn behavior using Kaplan–Meier curves, Log-Rank tests, and Cox Proportional Hazards models.
• Built Decision Tree and Random Forest models for churn prediction.
• Integrated survival probabilities into Customer Lifetime Value (LTV) estimation.
• Achieved a 56% reduction in estimated LTV, demonstrating overestimation when churn is ignored.