Abstract

This study conducts a comprehensive bibliometric examination to analyze Model-Based Customer Churn Research. Through Scopus, PRISMA, and VOSviewer. last two decades, academic publications and interest have increased. Empirical research, growth, and trends are examined in this paper. Evidence suggests churn prediction models using advanced data analytics, machine learning, and industry-specific methods. This shows scientific collaboration to predict industry churn. The study highlights "Expert Systems with Applications" and "ACM International Conference Proceedings Series," which spurred field dialogue. These publications provide cutting-edge research and expert opinions. Geographically, we study China, India, and the US. Global churn research matters. Bibliometric research shows model-based customer churns evolve. The resource can help academic and business researchers develop innovative client retention methods in different markets. By analyzing Model-Based Customer Churn the research studies, growth, and trends are examined. Evidence suggests churn prediction models use advanced data analytics, machine learning, and industry-specific methods. This shows scientific collaboration to predict industry churn. The study highlights "Expert Systems with Applications" and "ACM International Conference Proceedings Series," which spurred field dialogue. These publications provide cutting-edge research and expert opinions. Geographically, we study China, India, and the US. Global churn research matters. Bibliometric research shows that model-based customer churns evolve. The resource significantly assists academic and business researchers in developing innovative client retention methods in different markets.