Predicting Customer Churn In Telecom Industry: A Machine Learning Approach For Improving Customer Retention

In this research paper, we aim to analyze the factors that contribute to customer churn in the telecom industry and develop effective retention strategies to reduce churn rates and improve customer satisfaction. Ourfindings can help telecom companies develop effective retention strategies to reduce customer churn and improve customer satisfaction while maintaining affordable pricing for their services. The machine learning model we developed can be used as a tool for telecom companies to predict and prevent customer churn, leading to improved revenue and profitability. In addition to investigating the factors leading to customer churn, we propose a novel machine learning model that leverages advanced predictive analytics to identify at-risk customers and personalize retention interventions, further enhancing its applicability for telecom companies seeking to mitigate churn and foster long-term customer loyalty. Our research provides actionable insights and a comprehensive approach towards sustainable growth in the highly competitive telecom industry.“