Research on Machine Learning-Driven Customer Churn Warning and Retention Optimization Strategy for SMEs
DOI:
https://doi.org/10.70088/rhps4d46Keywords:
Customer Churn, Machine Learning, Retention Strategies, SMEs, Predictive AnalyticsAbstract
This research article explores the application of machine learning techniques to predict customer churn and optimize retention strategies for small and medium-sized enterprises (SMEs). By leveraging predictive analytics, the study aims to provide actionable insights into customer behavior, enabling SMEs to proactively address churn risks and enhance customer loyalty. The paper outlines a systematic approach, including model development, evaluation, and strategy optimization, to empower SMEs in sustaining competitive advantage in dynamic markets.References
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Copyright (c) 2026 Zhijun Liu (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
