Data-Driven Strategies for Enhancing Customer Retention in Moroccan Telecoms

Abstract

In the face of escalating customer turnover, Moroccan telecom operators seek robust strategies to retain their customer base. This chapter investigates the dynamics of customer churn and proposes a big data analytic approach to predict and minimize this phenomenon. Through the integration of logistic regression, machine learning techniques, and psychological profiling, the authors provide a comprehensive model for understanding customer behaviors and developing targeted retention strategies. The findings from this study offer a valuable blueprint for telecom companies to not only address the churn but to also pave the way for sustained market success in a competitive digital economy.