Machine Learning Models for Customer Segmentation in Telecom

This paper throws light upon the role of machine learning in refining customer segmentation for telecom organizations. Customer segmentation becomes a critical initiative for telecom companies to tailor respective services and customer experience. It discusses the distinction between traditional and advanced machine learning models, including supervised, unsupervised, and hybrid models that are compared in terms of segmentation methods, data requirements, and model evaluation techniques. The article delves into machine learning capabilities to help differentiate customers with enhanced accuracy, thus illuminating insights into business strategies, implementation challenges, and future trends in telecom analytics.