本文關鍵詞： 電商企業(yè) 客戶流失 風險預警 主成分分析 神經網絡　出處：《青島科技大學》2017年碩士論文　論文類型：學位論文

【摘要】：在我國電商企業(yè)迅猛發(fā)展的形勢下,企業(yè)逐漸將競爭的焦點轉移到客戶資源的爭奪上。伴隨著電商企業(yè)對客戶資源爭奪競爭激烈程度的加大,客戶越來越處于一種不穩(wěn)定的狀態(tài),導致各電商企業(yè)由于頻繁且大量的客戶流失延長了企業(yè)利潤的回收周期。在這種各大電商面臨客戶流失問題的大數(shù)據(jù)形勢下,電商企業(yè)需要將關注的重點聚焦在如何根據(jù)客戶已經體現(xiàn)出的個體特性及發(fā)生的行為規(guī)律預測企業(yè)未來可能發(fā)生的流失情況,并結合這些規(guī)律制定出行之有效的應對措施,以使企業(yè)適應競爭環(huán)境的變化、更加接近企業(yè)利益最大化的目標,這同時也是電子商務信息管理領域的一個重要課題。為了根據(jù)客戶個體和行為規(guī)律預測企業(yè)未來的客戶流失,十分關鍵且首要的一步是了解影響企業(yè)客戶流失的風險影響因素。針對這點,論文在理論研究的基礎上結合訪談的方法得到可能影響電子商務企業(yè)客戶流失的重要因素,構成客戶流失風險預警指標體系,并以調查問卷的方式對目標電商平臺使用人群進行調查,獲取研究所需樣本數(shù)據(jù)。在問卷調查之后的研究過程中,應用科學的方法對調查問卷的信度和效度進行檢驗。隨后應用主成分分析方法提取出與電商企業(yè)客戶流失關系最大最有代表性的指標,作為客戶流失風險預警模型的輸入層,根據(jù)聚類分析得到的四個不同客戶流失風險預警等級作為模型輸出層,構建了電商企業(yè)客戶流失風險預警模型。最后,在檢驗了模型的正確性之后,在文章研究基礎上提出電商企業(yè)應對客戶流失風險不同警情的防范和控制建議。
[Abstract]:With the rapid development of e-commerce enterprises in China, enterprises gradually shift the focus of competition to the competition of customer resources. Customers are increasingly in an unstable state. As a result of frequent and a large number of customer turnover, e-commerce enterprises have extended the profit recovery cycle. Under this situation, e-commerce companies are faced with customer churn problem in big data situation. Ecommerce enterprises need to focus on how to predict the loss of enterprises in the future according to the individual characteristics and behavior rules of customers. In order to adapt to the change of the competitive environment, and to make the enterprises more close to the goal of maximizing the interests of enterprises, the effective countermeasures are worked out in combination with these laws. This is also an important subject in the field of e-commerce information management. In order to predict the future customer turnover according to the individual and behavior rules of customers. A key and first step is to understand the risk factors that affect customer turnover. On the basis of theoretical research, this paper combines the method of interview to get the important factors that may affect the customer turnover of e-commerce enterprises, and constitutes the early warning index system of customer churn risk. And by the way of questionnaire to the target ecommerce platform users of the survey to obtain the research needs of the sample data. In the research process after the questionnaire. The reliability and validity of the questionnaire were tested by using scientific methods. Then principal component analysis was used to extract the largest and most representative indicators of customer turnover in e-commerce enterprises. As the input layer of the customer churn risk early warning model, according to the four different customer loss risk warning levels obtained by cluster analysis as the model output layer, an e-commerce enterprise customer loss risk warning model is constructed. Finally. After checking the correctness of the model, this paper puts forward some suggestions on how to prevent and control the different situations of customer churn risk in e-commerce enterprises on the basis of the research in this paper.
【學位授予單位】：青島科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F724.6;F274

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本文編號：1465719