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Time Series Churn Prediction
A telecom company was experiencing high customer churn. The goal was to build a model to predict which customers were most likely to churn.
The Challenge
A telecom company was experiencing high customer churn. The goal was to build a model to predict which customers were most likely to churn.
Approach & Methodology
Utilized time-series analysis on customer usage data. Developed a machine learning model using Logistic Regression and Gradient Boosting.
Solution & Results
The model achieved 85% accuracy in predicting churn. Delivered a dashboard visualizing key churn indicators.
Business Impact
Enabled proactive customer retention campaigns targeting at-risk customers, projected to reduce churn by 15%.