Telecom Sector Churn Prediction Using Decision Tree and Random Forest Models

Abstract

Telecommunication sector is an important industry in upcoming developing countries. The Tech progress, the rapid increase in the number of operators raising the competition of the industry. Customer churn is Leading as one biggest problem of mobile phone companies as it can have a significant impact on sales and revenue. Loss can happen for a variety of reasons, including switching to a competitor, canceling a subscription due to bad customer service, or severing a relationship with a company because there is a link. Churn might be because to various factors, including switching other company, cancelling subscription because of poor customer service, or maybe not continuing all contact with a brand because of insufficient touch-points. To meet this challenge, predictive modeling tools like decision trees and random forest are used to identify customers most likely to lose customers. In this study we examine how decision trees and random forests perform when it comes to predicting the communication skills of users. The research findings suggest that random forests are effective, in forecasting customer churn within the communications industry. Telecommunications companies can leverage this information to develop strategies aimed at retaining customers who are considering leaving.