基于RFM的网店客户价值细分研究
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摘要
在网店竞争越来越激烈的环境下,如何留住客户提高客户回头率非常关键,网店可以选择RFM(Regency、Frequency、Monetary)分析法对客户价值进行区分从而有针对性地对不同的客户提供营销服务。RFM分析法的应用首先通过SPSSStatistics软件包含的直销模块进行RFM建模,得出客户的RFM得分,然后再运用独立分箱或者嵌套分箱的方法进行客户价值的区分,从而网店可以对RFM得分不同的客户设计不同的营销策略。
In the environment of more and more fierce competition between online store, it is very important to retain customers and improve customer return rate. Online stores can choose RFM(Regency, Frequency, Monetary) analysis method to distinguish customer value, so as to provide marketing services for different customers. The application of RFM first makes RFM modeling through the direct selling module contained in the SPSS Statistics software, obtains the customer's RFM score, and then uses the separate box or nested sub box to distinguish the customer value, thus the online store can design the different marketing strategies for the customers with different RFM scores.
In the environment of more and more fierce competition between online store, it is very important to retain customers and improve customer return rate. Online stores can choose RFM(Regency, Frequency, Monetary) analysis method to distinguish customer value, so as to provide marketing services for different customers. The application of RFM first makes RFM modeling through the direct selling module contained in the SPSS Statistics software, obtains the customer's RFM score, and then uses the separate box or nested sub box to distinguish the customer value, thus the online store can design the different marketing strategies for the customers with different RFM scores.
引文
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[2]魏建国.RFM模型在商业银行客户行为分析中的应用[J].中国金融电脑,2011(6):40-43.
[3]马宝龙,李金林,李纯青,王高.随机RFM模型及其在零售顾客价值识别中的应用[J].管理科学与工程,2011(01):102-108.
[4]郦瞻.网络营销[M].北京.清华大学出版社,2013.
[5]姜缘意.基于RFM的丫商城客户细分及营销策略研究[D].辽宁:大连理工大学,2011.
[6]徐翔斌,王佳强,涂欢,穆明.基于改进RFM模型的电子商务客户细分[J].计算机应用,2011.
[7]刘朝华.基于客户价值的客户分类模型研究[D].湖北:华中科技大学,2008.
[8]安详茜.基于RFM模型的C2C环境下顾客价值识别研究[D].四川:西南财经大学,2012.
[9]中国互联网络信息中心.2018年中国互联网络发展状况统计报告[EB/OL]http://www.cnnic.cn/hlwfzyj/hlwxzbg/hlwtjbg/201803/P020180305409870339136.pdf.