Comparison of Main Algorithms in Big Data Analysis of Telecom Customer Retention

Abstract

Abstract In today’s fierce telecommunications market competition, customer chum is very severe. In order to retain customers, telecommunications companies have made various attempts from various data and consumption characteristics analysis to big data analysis. However, since the actual situation of customer churn is very complicated, how to predict customer churn accurately and quickly is a difficult problem. After the researchers successfully conducted big data analysis of customer churn and successfully retained customers, in this article, the researchers mainly compared several commonly used algorithms in order to find a better algorithm for big data analysis of telecommunications customer churn. Compare and analyze the accuracy and efficiency of these several algorithms and suggest that the business support staffs of telecommunications companies adopt major methods for big data analysis. The researcher found that the Decision Tree (CART) algorithm is better for the prediction of customer churn and guided other branch staffs to predict customer churn and retain customers in a timely manner. This kind of big data analysis can be used to retain customers in the telecommunications industry.