Enhancing Customer Retention Strategies: Predicting Churn Rate in Telecom Sectors Using Machine Learning Ensemble Techniques

In the competitive telecommunications industry, clients risk revenue and marketing costs. This study focuses on churn using ensemble methods such as RandomForest, ExtraTrees, LightGBM, and XGBoost. Evaluating eight algorithms including Decision Tree and Gradient Boosting, AdaBoost emerges as the best performer with the highest F1 score, ensuring a balanced trade-off between accuracy and recall He advises telecom companies on flying routes improving the storage of strategic importance, using machine learning. The findings provide a strategy for telecommunication companies to improve customer retention strategies in a dynamic market.