Customer churn prediction in telecom: enhancing customer retention strategies

Abstract

This thematic paper examines customer churn dynamics in the telecommunications industry, focusing on logistic regression as a predictive tool. Through an analysis of factors influencing churn and actionable insights for mitigation, the study aims to enhance customer retention and organizational resilience. Key findings reveal the significance of factors like contract terms, internet service, and total charges in predicting churn. Promising model performance, with an accuracy of approximately 78.82%, underscores the importance of proactive retention strategies. Recommendations include service improvements, promotion of long-term contracts, and targeted engagement initiatives to mitigate churn risk. While acknowledging limitations, the study suggests avenues for future research to refine models and explore customer motivations. In conclusion, actionable insights provided can empower telecom companies to navigate churn challenges and drive business growth in a competitive landscape.