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首页> 外文期刊>Journal of Engineering & Applied Sciences >Proposing a New Model for Determining the Customer Value Using RFM Model and its Developments (Case Study on the Alborz Insurance Company)
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Proposing a New Model for Determining the Customer Value Using RFM Model and its Developments (Case Study on the Alborz Insurance Company)

机译:提出使用RFM模型确定客户价值的新模型及其开发(Alborz Insurance Company的案例研究)

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摘要

The purpose of this study is to provide a model for clustering insurance customers so that we can found any uncertainties and risks regarding customer classes, as well as influential variables in their behavior. In this regard, information related to the car insurance in Alborz Insurance Company has been collected from 2009-2013. At the first we have studied and preprocessed data and then used RFM technique and two ARFM and SRFMA approaches as well as studying the risk of customers that is due to the compensation, using k and fuzzy k-means clustering methods, customer loyalty has been reviewed. Next, we studied RFM techniques and proposed approaches as well as risk of customers in combination with each other. Numerical results affirm the superiority of fuzzy based approaches which outperforms traditional ones in term of the accuracy measures. Considering risk factor as an addition to proposed RFM scheme, the measure was enhanced and increased by 8.41%.
机译:本研究的目的是为集群保险客户提供一个模型,以便我们可以找到有关客户课程的任何不确定性和风险,以及其行为中的有影响力的变量。 在这方面,从2009 - 2013年收集了与Alborz保险公司的汽车保险有关的信息。 首先,我们已经研究过的数据,然后使用RFM技术和两个ARFM和SRFMA方法以及研究由于补偿而导致的客户的风险,使用K和模糊K-Means聚类方法,客户忠诚度已被审查 。 接下来,我们研究了RFM技术和建议的方法以及客户的风险相结合。 数值结果肯定了基于模糊的方法的优越性,在准确度措施中优于传统的方法。 考虑到危险因素作为提出的RFM方案的补充,该措施得到了增强和增加了8.41%。

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