Title: Customer churn prediction based on customer value and user evaluation emotions in online marketing

Authors: Huanan Mo

Addresses: College of Economics and Management, Beibu Gulf University, Qinzhou, 535011, China; Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, 16150, Malaysia

Abstract: In order to improve the accuracy and usefulness of the churn prediction model, the core elements of the research content were designed to include collecting data on customer purchase behaviour and reviews, quantifying and analysing customer value, analysing customer sentiment in reviews, and combining customer value factors and review sentiment factors in the model. The results of the study show that the model performs best on different indicators, and the area of the main characteristic curve is the largest, which is significantly higher than that of the traditional model. Its hit rate, coverage rate and improvement coefficient also perform well. At the same time, when the sample size increases, the improvement coefficient increases the most, reaching 0.41. In conclusion, the model performs well in customer churn prediction, and it can provide certain reference value for the research field of customer churn prediction.

Keywords: online marketing; customer value; evaluate emotions; customer churn prediction; CCP; fusion model.

DOI: 10.1504/IJWBC.2025.145136

International Journal of Web Based Communities, 2025 Vol.21 No.1/2, pp.107 - 123

Received: 12 Jul 2023
Accepted: 07 Nov 2023
Published online: 21 Mar 2025 *

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