Triad Analytics: Churn, Anomalies, and CLV in Telecom using Machine learning

This paper presents the Triad Analytics framework that integrates three critical pillars of customer analytics: churn prediction, anomaly detection, and CLV estimation, offering a holistic approach to understanding customer dynamics using XGBoost, Random Forest, and SVMs. The findings equip telecommunications companies with powerful analytical tools to reduce churn, uncover hidden behavioral patterns, and optimize marketing strategies, fostering long-term customer loyalty and profitability in a competitive market [9]. This study also highlights opportunities for further refinement, addressing challenges like data imbalances to enhance model performance and practical applicability.