Keywords
User churn
Prediction model
Behavior analysis
Random forest
Submitted : 2025-05-07
Accepted : 2025-05-22
Published : 2025-06-06
Abstract
Customer churn has a significant impact on enterprises as it directly affects their revenue and profit. This paper focuses on analyzing user behavior data based on a machine learning-based user churn prediction model, constructs a prediction model, and verifies its effectiveness. This aims to help enterprises better understand user behavior and prevent user churn in advance. Meanwhile, by collecting and analyzing user data, multiple machine learning algorithms are used for modeling and evaluation to determine the optimal prediction model, which is then applied to practical business scenarios. The experimental results show that the model can accurately predict user churn, providing strong support for enterprises to develop personalized marketing strategies and enhancing user retention rates and enterprise competitiveness.
References
André B, Lin C, 2023, A Simple Model for Predicting User Churn. Journal of Economics and Management, 2(3): 111–134.
Wang Y, 2023, Applied Research on User Churn Prediction Based on Machine Learning Models, thesis, Changchun University of Technology.
Liu XQ, 2023, Research on Machine Learning in the User Churn Prediction Model of TV Shopping, thesis, China University of Geosciences (Beijing).
Wang DC, 2023, Research on the Communication User Churn Prediction Model Integrating GAN, thesis, Jiangxi Normal University.
Zheng GX, Xu K, 2022, User Churn Prediction Model for the Live-Streaming Industry Based on High-Dimensional Time-Series Feature Supplementation. Science and Technology & Innovation, 2022(23): 56–61.
Huang ZY, 2022, Research and Application of the User Churn Prediction Model for Private-Equity-Fund Wealth-Management APPs, thesis, University of International Business and Economics.
Hu YF, Xiong W, Gao W, 2022, A Method for Predicting the Churn of Online-Game Users Based on the Spark Platform. Computer Engineering and Science, 44(10): 1730–1737.
Huang ZX, 2022, Research on Telecommunication User Churn Prediction Model Based on Attention Mechanism, thesis, Hangzhou Dianzi University.
Zheng GX, 2022, Research and Application of User Churn Prediction Model for Live-streaming APPs Based on Data-Driven. South China University of Technology.
Xu SD, 2021, Research and Implementation of User Churn Prediction Model Based on MLP. Journal of Guangdong Communication Polytechnic, 20(3): 35–39 + 47.
Xie J, 2021, Research on Mobile Application User Churn Prediction Method Based on Hybrid Model, thesis, Wuhan University of Technology.
Liao W, 2020, Research and Application of Internet Finance User Churn Prediction Model Based on Data Mining, thesis, South China University of Technology.
He AS, Wang L, Huang S, 2020, Design and Implementation of User Churn Early-Warning System Based on Big Data. Radio & TV Information, 27(7): 93–94.
Wen RJ, 2020, Research on the Application of Deep Learning Models in Bank User Churn Prediction, thesis, Chongqing University of Posts and Telecommunications.
Wu HF, 2020, Research on User Portrait and Churn Prediction Model of UFIDA Based on Data Mining Methods, thesis, Dongbei University of Finance and Economics.