基于RFMF模型和K-Means方法的公募基金用户精细化营销
Meticulous Marketing of Mutual Fund Customers Based on RFMF Model and K-Means Method

DOI: 10.12677/FIN.2019.96070, PP. 634-640

Keywords: RFM模型，用户聚类，基金精细化营销
RFM Model, Customer Clustering, Meticulous Fund Marketing

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Abstract:

随着互联网技术的飞速发展，互联网渠道已经成为了公募基金公司重点耕耘的销售渠道。精细化的营销对于降低营销成本，提高运营效率至关重要。面对随着互联网成长起来的具有巨大理财潜力的用户，如何对其进行有效区分，并针对不同类型人群实施精细化的营销策略，是当前公募基金公司急需解决的问题。本文提出了改进的RFM模型，从近度、频度、管理费三个维度对用户价值进行衡量，并通过K-Means算法对用户进行聚类，从而实现用户分群。并使用了某基金公司的某产品的申赎历史数据对模型进行了验证，得到了5个聚类结果，并针对5个聚类中用户的特点，提出了具有针对性的营销策略。
With the rapid development of Internet technology, Internet channels have become the key sales channels for mutual fund companies. Meticulous marketing is critical to reduce costs and improve operational efficiency. Facing customers with huge financial potential growing up with the Internet, how to effectively distinguish them and implement meticulous marketing strategies for different types of customers is an urgent problem for the companies. This paper proposed an improved RFM model, which measures customer value from three dimensions of recency, frequency and management fee, and grouped users through K-Means algorithm. The model was verified by using the historical data of a certain fund company’s product, and five clusters were obtained. Based on the characteristics of users in the five clusters, targeted marketing strategies were proposed.

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