TITLE:
Research on User Profiling of “Internet + Nursing Service” Platform Based on Improved RFM Model
AUTHORS:
Yiliang Xie, Chen Chen, Rui Zhang
KEYWORDS:
Internet + Nursing Service, User Profiling, RFM, Two-Step Clustering, Random Forests
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.13 No.4,
April
23,
2025
ABSTRACT: Under the background of aging populations, constructing user portraits for the “Internet + Nursing Service” platform helps to deeply understand the demand characteristics of the elderly groups characteristics of elderly groups, laying a foundation for providing precise services. In this study, data from the nursing platform of Company X in Xi’an, extracted from the *Smart Health and Elderly Care Products and Services Promotion Catalogue (2022 Edition)*, were analyzed. User portraits were constructed by combining an improved RFM model with a two-step clustering algorithm, while the random forest algorithm was applied for model training and user identification. The results indicated that users could be categorized into three groups: loyal consumers, potential developers, and one-time users. Based on the classification outcomes, strategies such as promoting aging-friendly transformations, implementing refined marketing, and focusing on central urban areas were proposed to enhance the platform’s high-quality development and improve user experience and well-being.