Telecom Churn Prediction and Optimized Package Recommendation for Indian ISPs

Abstract: Customer attrition poses a critical threat to the Indiantelecomlandscape,impactingprofitabilityandintensifying the rivalry among key players like Jio, Airtel, Vi, and BSNL.This paper introduces a machine learning-based framework for forecastingcustomerchurnandrecommendingISPplanstailored touserbehavior,networkquality,andreal-timespeedtests. The system examines variables such as billing inconsistencies, dropped calls, sluggish data speeds, and customer grievances to pinpoint users likely to switch providers. To support decision- making, we also integrated a dynamic network speed checkerthat compares ISP performance across regions. Experimental outcomes reveal that the XGBoost model attained a 94% accu- racy rate in churn prediction, while the tailored plan suggestions significantly improved user satisfaction.