Customer Satisfaction-Driven Approach for Predicting Customer Churn in Online Video: Case of Guangxi Province, China

This study explores a customer satisfaction-driven approach for predicting customer churn in online video platforms within Guangxi Province, China.By analysing key satisfaction factorssuch as content quality, user experience, and pricing-the research identifies patterns influencing users' decisions to discontinue services.Using machine learning models, it demonstrates how integrating satisfaction metrics enhances churn prediction accuracy.Findings suggest that improving specific satisfaction dimensions significantly reduces churn rates.The study offers practical insights for video service providers to retain customers through targeted satisfaction strategies, contributing to sustainable user engagement and competitive advantage in the dynamic Chinese online video market.