Applicability of machine-learning techniques in predicting customer defection

Abstract

Machine learning is an established method of predicting customer defection from a contractual business. However, no systematic comparison or evaluation of the different machine-learning techniques has been performed. In this study, we provide a comprehensive comparison of different machine-learning techniques with three different data sets of a software company to predict customer defection. The evaluation criteria of the techniques are understandability of the model, convenience of using the model, time efficiency in running the learning model, and performance of predicting customer defection.