머신러닝 기반 고객 이탈 예측과 ERFM을 활용한 플랫폼 비즈니스의 고객 세분화 방법론
- 등록일
- 2025.06.15
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- 지식서비스연구소
초록 (Abstract)
Purpose : Platform businesses drive the digital economy through interactions and network effects but face challenges like customer churn. This study aims to develop a framework that evaluates both churn risk and customer value, optimizing marketing strategies and resource allocation. Methods : Churn prediction is conducted using machine learning algorithms, combined with the Extended RFM (ERFM) model, which evaluates recency, purchase frequency, monetary value, and engagement on the platform. This integrated approach assesses both the likelihood of churn and the overall value of each customer. Results :The proposed model identifies high-value customers and predicts churn with accuracy. It supports tailored marketing strategies that enhance resource efficiency and customer retention. Conclusion : By linking churn prediction with value assessment, the study offers insights to enhance customer loyalty, engagement, and profitability, ensuring competitive advantages for platform businesses.
한국경영공학회지 30(2), 1-16, 2025.6