發(fā)布時間：2018-06-27 13:18

  本文選題：數(shù)據(jù)挖掘 + 客戶關(guān)系管理��； 參考：《大連海事大學》2008年碩士論文

【摘要】： 數(shù)據(jù)挖掘技術(shù)在客戶關(guān)系管理(CRM)中的應(yīng)用作為近年來研究的熱點問題，已引起學術(shù)界和企業(yè)界的廣泛關(guān)注。CRM是將客戶信息轉(zhuǎn)化成為積極的客戶關(guān)系的反復(fù)循環(huán)過程，企業(yè)通過建立與客戶溝通的便利渠道，實施客戶關(guān)懷，為客戶創(chuàng)造更高的價值，來提高客戶的滿意度和忠誠度，從而實現(xiàn)更高的利潤和企業(yè)的長遠發(fā)展。數(shù)據(jù)挖掘則是從大量數(shù)據(jù)中發(fā)掘出有用知識的強有力工具，是實施客戶關(guān)系管理的關(guān)鍵技術(shù)之一。企業(yè)在收集大量的客戶基本資料和詳細的交易數(shù)據(jù)的基礎(chǔ)上，利用數(shù)據(jù)挖掘能夠發(fā)現(xiàn)客戶特征、客戶購買模式等有價值的客戶知識，可以有效地指導客戶關(guān)系管理實踐。 運營型CRM是以整合企業(yè)內(nèi)部資源為主，而分析型CRM旨在增加CRM系統(tǒng)的商業(yè)分析與輔助決策能力，為企業(yè)提供有價值的決策知識。因此本文主要研究如何把數(shù)據(jù)挖掘技術(shù)應(yīng)用到分析型CRM中去，，從而實現(xiàn)企業(yè)CRM系統(tǒng)中的分析決策功能。 本文首先對數(shù)據(jù)挖掘相關(guān)理論、CRM思想以及數(shù)據(jù)挖掘技術(shù)在CRM中的應(yīng)用進行了介紹，并引入了RFM和客戶價值矩陣理論。然后在運營型MBCRM系統(tǒng)的基礎(chǔ)上設(shè)計構(gòu)建分析型MBCRM系統(tǒng)。針對分析任務(wù)特點和企業(yè)需求，結(jié)合RFM和客戶價值矩陣的內(nèi)容，確定了客戶購買行為分類、客戶類別特征分析和客戶營銷分析三個主題的數(shù)據(jù)挖掘模式，提出了挖掘建模算法，設(shè)計了挖掘?qū)嵤┻^程，然后通過程序編碼得以實現(xiàn)，得出了許多啟發(fā)性規(guī)則。最后闡述了本課題研究中的一些心得和今后的研究展望。
[Abstract]:The application of data mining technology in customer relationship management (CRM), as a hot research issue in recent years, has aroused the widespread concern of academic and business circles. CRM is an iterative process of transforming customer information into positive customer relationship. Through the establishment of convenient channels of communication with customers, the implementation of customer care, to create higher value for customers, to improve customer satisfaction and loyalty, so as to achieve higher profits and long-term development of the enterprise. Data mining is a powerful tool to extract useful knowledge from a large amount of data, and it is one of the key technologies to implement customer relationship management. On the basis of collecting a large number of customer basic information and detailed transaction data, enterprises can find valuable customer knowledge such as customer characteristics, customer purchase patterns and so on by using data mining, which can effectively guide the practice of customer relationship management. The operational CRM is to integrate the internal resources of the enterprise, while the analytical CRM aims to increase the ability of business analysis and auxiliary decision making of CRM system, and to provide valuable decision-making knowledge for the enterprise. Therefore, this paper mainly studies how to apply data mining technology to analytical CRM, so as to realize the function of analysis and decision in enterprise CRM system. Firstly, this paper introduces the CRM theory and the application of data mining technology in CRM, and introduces RFM and customer value matrix theory. Then, an analytical MBCRM system is designed and constructed on the basis of operational MBCRM system. According to the characteristics of the analysis task and the requirements of the enterprise, combined with the content of RFM and customer value matrix, this paper determines the data mining patterns of customer purchase behavior classification, customer class feature analysis and customer marketing analysis, and puts forward a mining modeling algorithm. The mining implementation process is designed, and then realized by program coding, and many enlightening rules are obtained. In the end, some experiences and future research prospects of this research are described.
【學位授予單位】：大連海事大學
【學位級別】：碩士
【學位授予年份】：2008
【分類號】：TP311.13

【引證文獻】

相關(guān)期刊論文 前1條

1 來羽;;基于分類算法的可視化技術(shù)研究[J];煤炭技術(shù);2010年10期

相關(guān)碩士學位論文 前5條

1 閔銳;數(shù)據(jù)挖掘在CRM中的應(yīng)用研究[D];長春工業(yè)大學;2010年

2 徐勇;分析型CRM中聚類算法的研究[D];蘭州理工大學;2010年

3 劉中賀;件煙自動補貨算法研究[D];北京郵電大學;2010年

4 趙裕嘯;基于OLAM的分析型CRM及其在證券業(yè)的應(yīng)用研究[D];合肥工業(yè)大學;2010年

5 劉建蘭;數(shù)據(jù)挖掘技術(shù)在客戶關(guān)系管理中的應(yīng)用研究[D];南昌大學;2010年

本文編號：2074041