Machine Learning - Based Customer Retention System for Telecom

Prof. Nilesh Mishra; Muskan Bisone; Kiran Dhurve; Nikhil Mankar

Machine Learning - Based Customer Retention System for Telecom

Author(s)	Prof. Nilesh Mishra, Muskan Bisone, Kiran Dhurve, Nikhil Mankar
Country	India
Abstract	Customer churn is a serious issue in the telecommunications industry because losing customers reduces company revenue and increases the cost of acquiring new customers. The main objective of this project is to develop a Customer Churn Prediction System that can identify customers who are likely to leave telecom services. The system helps companies take preventive actions by predicting churn in advance and categorizing customers into High, Medium, and Low risk groups. In this project, a telecom customer dataset containing customer details, service usage information, billing data, and contract type was used. The data was cleaned and prepared using preprocessing techniques such as handling missing values and encoding categorical variables. Machine learning algorithms including Logistic Regression, Random Forest, and XGBoost were implemented to predict whether a customer will churn or not. The models were evaluated using performance metrics such as accuracy, precision, recall, and confusion matrix to select the most suitable model. The system provides two prediction methods. The first method allows users to manually enter customer details and obtain churn probability, model confidence score, and risk classification. The second method allows bulk prediction by uploading a CSV file, where users can preview the data and download results in table format. The output includes churn probability, confidence level, risk category, and key features influencing churn. An interactive dashboard is also provided for graphical analysis of churn trends. The results show that machine learning can effectively predict customer churn and support better decision-making in the telecom sector.
Keywords	Customer Churn, Telecom, Predictive Modeling, Explainable AI, Dashboard.
Field	Engineering
Published In	Volume 17, Issue 4, April 2026
Published On	2026-04-09
Cite This	Machine Learning - Based Customer Retention System for Telecom - Prof. Nilesh Mishra, Muskan Bisone, Kiran Dhurve, Nikhil Mankar - IJTAS Volume 17, Issue 4, April 2026.

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Machine Learning - Based Customer Retention System for Telecom

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