文献综述——基于RFM模型的顾客行为分析

Putu Aryasuta Wicaksana, I. B. A. Swamardika, R. S. Hartati
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引用次数: 1

摘要

摘要--数据是每个公司的资产,尤其是客户数据。下文中对客户数据的处理可以称为数据挖掘。当前行业的激烈竞争使得公司在处理客户数据时必须小心,其中之一就是为CRM运营处理客户数据。目的是通过分析客户行为来识别客户。因此,这可能是公司的一项投资。可以使用RFM模型来预测客户行为。在这种情况下,作者对RFM模型在数据挖掘中的实现进行了研究,以帮助企业更好地了解他们的客户。从审查结果来看,2016-2021年的RFM模型更多地与数据挖掘技术相结合,即聚类算法,其目标是对客户进行分组或细分。从综述的结果中,作者还阐述了可以做的研究,即将RFM模型与TOPSIS方法相结合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Literature Review Analisis Perilaku Pelanggan Menggunakan RFM Model
Abstract— Data is an asset for every company, especially Customer Data. Processing of customer data hereinafter can be referred to as Data Mining. The current tight competition in the industry makes companies have to be careful in processing their customer data, one of which is processing customer data for CRM operations. With the aim of recognizing customers by analyzing customer behavior. So this can be an investment for the company. Customer behavior can be predicted using the RFM model. And on this occasion, the author conducts a study on the implementation the RFM Model in data mining in helping companies to better understand their customers. From the results of the review, the RFM model in the 2016-2021 range, it is more combined with data mining techniques, namely the clustering algorithm, where the goal is to group or segment customers. And from the results of the review, the author also formulates research that can be done, namely combining the RFM model with the TOPSIS method.
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