客户集群的RFM-FCM方法

Toly Chen
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引用次数: 4

摘要

RFM模型是客户聚类的重要方法。Chiu和Su(2004)提出了一种模糊RFM模型来克服传统RFM模型的不足。然而,在邱和苏的方法中还有一些问题没有解决。例如,无法预先指定客户集群的数量;在形成客户集群时,没有考虑到客户数据的内在结构,这些结构对企业来说是未知的但有价值的信息。为了解决这些问题,本文结合基于数据本身固有结构的模糊c均值方法,提出了一种模糊RFM模型。考虑到营销资源的稀缺性和营销策略的多样化,客户集群的数量可以预先任意指定。此外,探索每个客户群的内容为企业提供了许多有意义的建议,这些建议可以有效地用于制定目标营销方案。本文以Chiu和Su的研究为例,论证了所提出方法的应用,并进行了一些比较。
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The RFM-FCM approach for customer clustering
RFM model is an important method in customer clustering. Chiu and Su (2004) proposed a fuzzy RFM model to overcome the shortcomings of traditional RFM models. However, there are some problems unsolved in Chiu and Su's approach. For example, the number of customer clusters cannot be specified in advance; the inherent structure of customer data which is unknown yet valuable information to the business is not considered in forming customer clusters. To deal with these problems, a fuzzified RFM model is proposed in this study by incorporating the fuzzy c–means approach, which is based on the inherent structure of the data itself. The number of customer clusters can be arbitrarily specified in advance, considering the scarcity of marketing resources and the diversification of marketing strategies. Besides, exploring the content of each customer cluster provides the business with many meaningful suggestions that could be usefully employed to establish target marketing programmes. The example in Chiu and Su's study is adopted to demonstrate the application of the proposed methodology and to make some comparisons.
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来源期刊
International Journal of Technology Intelligence and Planning
International Journal of Technology Intelligence and Planning Business, Management and Accounting-Management of Technology and Innovation
CiteScore
3.20
自引率
0.00%
发文量
2
期刊介绍: The IJTIP is a refereed journal that provides an authoritative source of information in the field of technology intelligence, technology planning, R&D resource allocation, technology controlling, technology decision-making processes and related disciplines.
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