發(fā)布時(shí)間：2018-01-26 13:22

  本文關(guān)鍵詞： 電商企業(yè) 客戶流失 風(fēng)險(xiǎn)預(yù)警 主成分分析 神經(jīng)網(wǎng)絡(luò)　出處：《青島科技大學(xué)》2017年碩士論文　論文類型：學(xué)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(diǎn)轉(zhuǎn)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(dǎo)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(guān)注的重點(diǎn)聚焦在如何根據(jù)客戶已經(jīng)體現(xiàn)出的個(gè)體特性及發(fā)生的行為規(guī)律預(yù)測企業(yè)未來可能發(fā)生的流失情況,并結(jié)合這些規(guī)律制定出行之有效的應(yīng)對措施,以使企業(yè)適應(yīng)競爭環(huán)境的變化、更加接近企業(yè)利益最大化的目標(biāo),這同時(shí)也是電子商務(wù)信息管理領(lǐng)域的一個(gè)重要課題。為了根據(jù)客戶個(gè)體和行為規(guī)律預(yù)測企業(yè)未來的客戶流失,十分關(guān)鍵且首要的一步是了解影響企業(yè)客戶流失的風(fēng)險(xiǎn)影響因素。針對這點(diǎn),論文在理論研究的基礎(chǔ)上結(jié)合訪談的方法得到可能影響電子商務(wù)企業(yè)客戶流失的重要因素,構(gòu)成客戶流失風(fēng)險(xiǎn)預(yù)警指標(biāo)體系,并以調(diào)查問卷的方式對目標(biāo)電商平臺使用人群進(jìn)行調(diào)查,獲取研究所需樣本數(shù)據(jù)。在問卷調(diào)查之后的研究過程中,應(yīng)用科學(xué)的方法對調(diào)查問卷的信度和效度進(jìn)行檢驗(yàn)。隨后應(yīng)用主成分分析方法提取出與電商企業(yè)客戶流失關(guān)系最大最有代表性的指標(biāo),作為客戶流失風(fēng)險(xiǎn)預(yù)警模型的輸入層,根據(jù)聚類分析得到的四個(gè)不同客戶流失風(fēng)險(xiǎn)預(yù)警等級作為模型輸出層,構(gòu)建了電商企業(yè)客戶流失風(fēng)險(xiǎn)預(yù)警模型。最后,在檢驗(yàn)了模型的正確性之后,在文章研究基礎(chǔ)上提出電商企業(yè)應(yīng)對客戶流失風(fēng)險(xiǎn)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(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F724.6;F274

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本文編號：1465719