The focal point of this project is the mitigation of customer churn. Our objective is to construct a predictive model that effectively identifies customers at a high risk of discontinuing their services. Through the lens of data analytics, we endeavor to address the following key questions:
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Identification of Influential Factors: Uncover the pivotal factors influencing customer churn within the dynamic landscape of the telecom sector.
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Predictive Model Development: Devise a robust predictive model capable of early detection, pinpointing customers prone to churn based on historical data and leveraging Supervised Machine Learning (ML) techniques.
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Retention Strategy Exploration: Explore and propose targeted retention initiatives for telecom companies, harnessing the insights derived from our predictive model to minimize churn rates effectively.
The project report, along with the implementation code for each model, has been provided for your reference.