Harshitha .N
Data Analysis | Data Cleaning | Python | SQL | ML | Power BI
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The image shows the real-time output of the Customer Churn Prediction System. Based on the customer’s details, the model calculates the churn probability and categorizes the risk level (Medium / High / Very High). It also provides a clear risk assessment to help businesses identify customers who may leave and take early retention actions. The model achieves 94% accuracy with an AUC score of 96%.
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Developed a machine learning-based Customer Churn Prediction System that analyzes customer data and predicts the probability of churn in real time.
The system provides risk levels (Low, Medium, High, Very High) along with churn probability to help businesses take proactive retention actions.
Key Features:
• Real-time churn prediction through an interactive web interface
• Model Accuracy: 94% | AUC: 96%
• Risk assessment with actionable business insights
• Customer behavior analysis based on usage and service patterns
Business Impact:
Helps organizations identify high-risk customers early and reduce revenue loss through targeted retention strategies.
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