Title: Customer relationship value evaluation method for e-commerce platform based on fuzzy clustering

Authors: Sanping Qiu

Addresses: Department of Economics and Management, Jiyuan Vocational and Technical College, Ji'yuan, 459000, China

Abstract: In order to improve the accuracy of customer relationship value evaluation on e-commerce platforms and reduce evaluation time, this paper proposes a fuzzy clustering-based customer relationship value evaluation method for e-commerce platforms. Firstly, consider the changes in customer relationships at different stages of the lifecycle and analyse the timeliness characteristics of customer relationships. Then, the Weibull distribution function is introduced to calculate the length of customer lifecycle. Finally, cluster the investment return on tangible assets of the enterprise, and invert the investment return on intangible assets of the enterprise. Use fuzzy clustering to evaluate the customer relationship value and obtain the final evaluation result. The results show that the method proposed in this paper can effectively improve evaluation efficiency and evaluation efficiency, with an evaluation time of only 2.8 seconds and an evaluation accuracy of up to 99.6%.

Keywords: fuzzy clustering; e-commerce platform; customer relationship value evaluation; life cycle length; return rate splitting method.

DOI: 10.1504/IJWBC.2024.142477

International Journal of Web Based Communities, 2024 Vol.20 No.3/4, pp.311 - 322

Received: 29 May 2023
Accepted: 10 Oct 2023
Published online: 04 Nov 2024 *

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