Intelligent Churn Prediction Using In E-Commerce Using Conversational Analytics

Businesses must compete fiercely to win over new consumers from suppliers. Since it directly affects a company’s revenue, client retention is a hot topic for analysis, and early detection of client churn enables businesses to take proactive measures to keep customers. Consequently, this study aims to advise on the optimum machine-learning strategy for early client churn prediction. The goal is to predict existing customers’ responses to keep them. The study has tested algorithms like stochastic gradient booster, random forest, logistics regression, and K-Nearest Neighbours methods. The accuracy of the aforementioned algorithms are 83.9%, 82.6%, 82.9% and 78.1% respectively. We have acquired the most effective results by examining these algorithms and discussing the best among the four from different perspectives.