基于SOM的4S店客户细分及变化挖掘研究

发布时间：2018-03-06 06:45

本文选题：客户关系管理　切入点：客户细分　出处：《大连理工大学》2013年硕士论文　论文类型：学位论文

【摘要】：随着我国汽车行业的飞速发展,汽车厂家间的竞争日趋激烈,在汽车保有量急剧增长的同时,汽车售后服务的市场也随之变得越来越大。汽车厂家之间的竞争也已经由汽车的销售竞争转移到了售后服务的竞争。汽车4S店的售后维修服务部门作为汽车厂家与车主维系客户关系的重要部门,需要加速建设以客户为中心,以信息系统为基础的客户关系管理体系。4S店售后维修服务部门的服务对象是保有其品牌车系的全部车主,如何对这一庞大的客户群体进行有针对性的客户细分是4S店售后维修服务部门进行良好客户关系管理的基础。随着数据挖掘技术在商业环境中的应用越来越广泛,4S店售后维修服务部门也希望能够利用先进的数据挖掘技术来支持企业的客户细分和客户关系管理政策的制定。本研究把应用数据挖掘技术进行4S店客户细分过程看作知识发现过程,针对汽车售后维修服务业的特点,提出了适合于该行业企业的客户细分方法与客户群变化挖掘方法,以帮助企业更高效地进行客户关系管理。本文研究的主要内容包括： (1)在分析现有客户细分理论的基础上,结合汽车售后维修交易记录的特点,选择适合于4S店的基于客户行为的客户细分指标,并给出了从企业数据库中获得这些指标的方法。 (2)分别提出了运用自组织映射(Self-Organizing Maps, SOM)神经网络分阶段进行客户细分的方法和运用演化自组织映射(Evolving Self-Organizing Maps, ESOM)神经网络对客户进行在线细分的方法,并结合客户生命周期与价值矩阵模型对聚类结果进行分析与识别,得到易于服务人员及管理者理解的客户细分结果。 (3)在客户细分结果的基础上,分别从客户群和客户个体两个角度对客户随时间变化情况进行了分析。在客户群体角度提出了客户群在群数量及群属性上随时间变化的分析方法,在客户个体角度运用关联分析对客户个体的分群演变规律进行挖掘,得到处于不同阶段的客户的主要转移路径。
[Abstract]:With the rapid development of automobile industry in China, the competition among automobile manufacturers is becoming more and more fierce. The market of automobile after-sales service has also become larger and bigger. The competition among automobile manufacturers has also shifted from the competition of automobile sales to the competition of after-sales service. An important department that maintains customer relationships with car owners, There is a need to accelerate the construction of a customer-centric, information-system-based customer relationship management system. How to segment this huge customer group is the basis of 4S store after-sales maintenance service department for good customer relationship management. With the application of data mining technology in the business environment more and more widely. 4Shop after-sales maintenance services also hope to be able to use advanced data mining technology to support customer segmentation and customer relationship management policy formulation. In this study, the process of customer segmentation in 4S shop is regarded as the process of knowledge discovery. According to the characteristics of automobile after-sales maintenance service industry, the method of customer segmentation and customer group change mining suitable for the enterprises in this industry are put forward. In order to help enterprises to carry out customer relationship management more efficiently. The main contents of this paper include:. 1) based on the analysis of the existing customer segmentation theory and the characteristics of the automobile after-sales maintenance transaction record, this paper selects the customer segmentation index based on customer behavior suitable for 4S store, and gives the method of obtaining these indexes from the enterprise database. (2) A method of customer segmentation by using self-organizing mapping self-organizing maps (SOM) neural network and evolutionary self-organizing mapping Self-Organizing maps (ESOM) neural network is presented respectively. Combined with the customer life cycle and value matrix model, the clustering results are analyzed and identified, and the customer segmentation results which are easy to be understood by service personnel and managers are obtained. On the basis of the result of customer segmentation, this paper analyzes the change of customer with time from two angles of customer group and customer individual, and puts forward the analysis method of customer group changing with time in terms of quantity and attribute of customer group. In the perspective of customer individual, the association analysis is used to excavate the evolution rule of customer individual, and the main transfer path of customer at different stages is obtained.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F426.471;F224

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