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  本文選題：客戶關系管理　切入點：客戶細分　出處：《大連理工大學》2013年碩士論文　論文類型：學位論文

【摘要】：隨著我國汽車行業(yè)的飛速發(fā)展,汽車廠家間的競爭日趨激烈,在汽車保有量急劇增長的同時,汽車售后服務的市場也隨之變得越來越大。汽車廠家之間的競爭也已經(jīng)由汽車的銷售競爭轉移到了售后服務的競爭。汽車4S店的售后維修服務部門作為汽車廠家與車主維系客戶關系的重要部門,需要加速建設以客戶為中心,以信息系統(tǒng)為基礎的客戶關系管理體系。4S店售后維修服務部門的服務對象是保有其品牌車系的全部車主,如何對這一龐大的客戶群體進行有針對性的客戶細分是4S店售后維修服務部門進行良好客戶關系管理的基礎。隨著數(shù)據(jù)挖掘技術在商業(yè)環(huán)境中的應用越來越廣泛,4S店售后維修服務部門也希望能夠利用先進的數(shù)據(jù)挖掘技術來支持企業(yè)的客戶細分和客戶關系管理政策的制定。 本研究把應用數(shù)據(jù)挖掘技術進行4S店客戶細分過程看作知識發(fā)現(xiàn)過程,針對汽車售后維修服務業(yè)的特點,提出了適合于該行業(yè)企業(yè)的客戶細分方法與客戶群變化挖掘方法,以幫助企業(yè)更高效地進行客戶關系管理。本文研究的主要內(nèi)容包括： (1)在分析現(xiàn)有客戶細分理論的基礎上,結合汽車售后維修交易記錄的特點,選擇適合于4S店的基于客戶行為的客戶細分指標,并給出了從企業(yè)數(shù)據(jù)庫中獲得這些指標的方法。 (2)分別提出了運用自組織映射(Self-Organizing Maps, SOM)神經(jīng)網(wǎng)絡分階段進行客戶細分的方法和運用演化自組織映射(Evolving Self-Organizing Maps, ESOM)神經(jīng)網(wǎng)絡對客戶進行在線細分的方法,并結合客戶生命周期與價值矩陣模型對聚類結果進行分析與識別,得到易于服務人員及管理者理解的客戶細分結果。 (3)在客戶細分結果的基礎上,分別從客戶群和客戶個體兩個角度對客戶隨時間變化情況進行了分析。在客戶群體角度提出了客戶群在群數(shù)量及群屬性上隨時間變化的分析方法,在客戶個體角度運用關聯(lián)分析對客戶個體的分群演變規(guī)律進行挖掘,得到處于不同階段的客戶的主要轉移路徑。
[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.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F426.471;F224

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本文編號：1573749