客户关系管理中数据仓库技术应用研究
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摘要
电子商务的飞速发展,使传统的商业模式受到了严峻的挑战,它要求企业以全新的思维来看待客户。在这种情况下,客户关系管理得到了广泛的应用和发展,它为企业提供了收集、分析和利用各种客户信息的应用系统,以及企业面对客户的科学手段和方法,使企业的销售理念从以产品为中心转换到以客户为中心。目前传统的CRM信息系统产生大量的客户特征信息和客户行为信息,但是这些信息仅仅局限于表面的数据记载,缺少深层次的分析,并且随着企业规模和基础数据的不断增加,对于客户的管理也越来越难,因此,运用数据仓库技术构建分析型CRM系统就显得尤为重要。
数据仓库是一种数据集成分析技术,它能将企业各个级别数据库中的数据集成到一起,并最终以数据立方体的形式展现给最终用户,实现多维度分析,能够快速、直观的将决策信息提供给企业管理者,成为企业进行决策的有利工具,数据仓库作为CRM的底层核心,在未来企业的商务智能中发挥的作用会越来越大。
本文研究了数据仓库技术在企业分析型CRM中的应用,根据电子商务企业的特殊应用背景,设计了面向客户、订单、销售三个粒度的主题数据仓库,利用SQL Server2000为数据仓库的物理存储,提供强大的存储功能和检索功能；应用开源OLAP引擎Mondrian作为OLAP服务器,提供强大的多维分析功能；利用OPENI作为前端的分析展现工具,提供多维前端展示。最终通过数据仓库技术实现分析型CRM,并重点对客户价值、客户分级以及客户流失进行多维分析,为企业管理层的决策提供信息支持,并在应用中,验证以上模型和方法的有效性。
The rapid growth of E-commerce presents a severe challenge for the traditional enterprises, which requires enterprises to regard clients with new thinking. In this background, customer relationship management has been widely used and developed, which provides enterprises application system to collect、analyze and exploit customer information,and scientific methods to manage customers. It changes company's marketing concept from product-centric to customer-centric. Traditional CRM information systems produce a large amount of customer characteristic information and customer behavior information, but the information is only limited to original data records and lack of deep analysis, with increasing firm size and volume of basic data, management of customers become more and more difficult. Therefore, the application of data warehouse technology to build an analytical CRM system is particularly important.
Integrated data warehouse is a data analysis technique. It can integrate all levels of data in enterprise database together and eventually form a data cube to show to end users. It can realize multi-dimensional analysis, and provide decision-making information for enterprise managers fast and intuitively. It becomes a powerful tool for decision-making. As the basic core of CRM, data warehouse will become more important in the field of business intelligence in future.
This paper studies the application of data warehouse technologies in enterprise CRM. According to the particular background of technologies application data warehouse with themes of customers, orders and others are built, using SQL Server 2000 to provide powerful storage and retrieval. This work takes open source OLAP engine Mondrian as the OLAP server o provide powerful multi-dimensional analysis, and employs OPENI as the front end of the analysis tools to provide multi-dimensional front-end display. Finally analytic CRM based on data warehouse technologies CRM. Multi-dimensional analysis customer value, customer classification and customer churn. It provides information to support decision-making for enterprise managers, and verify the validity of these models and methods in the application.
数据仓库是一种数据集成分析技术,它能将企业各个级别数据库中的数据集成到一起,并最终以数据立方体的形式展现给最终用户,实现多维度分析,能够快速、直观的将决策信息提供给企业管理者,成为企业进行决策的有利工具,数据仓库作为CRM的底层核心,在未来企业的商务智能中发挥的作用会越来越大。
本文研究了数据仓库技术在企业分析型CRM中的应用,根据电子商务企业的特殊应用背景,设计了面向客户、订单、销售三个粒度的主题数据仓库,利用SQL Server2000为数据仓库的物理存储,提供强大的存储功能和检索功能；应用开源OLAP引擎Mondrian作为OLAP服务器,提供强大的多维分析功能；利用OPENI作为前端的分析展现工具,提供多维前端展示。最终通过数据仓库技术实现分析型CRM,并重点对客户价值、客户分级以及客户流失进行多维分析,为企业管理层的决策提供信息支持,并在应用中,验证以上模型和方法的有效性。
The rapid growth of E-commerce presents a severe challenge for the traditional enterprises, which requires enterprises to regard clients with new thinking. In this background, customer relationship management has been widely used and developed, which provides enterprises application system to collect、analyze and exploit customer information,and scientific methods to manage customers. It changes company's marketing concept from product-centric to customer-centric. Traditional CRM information systems produce a large amount of customer characteristic information and customer behavior information, but the information is only limited to original data records and lack of deep analysis, with increasing firm size and volume of basic data, management of customers become more and more difficult. Therefore, the application of data warehouse technology to build an analytical CRM system is particularly important.
Integrated data warehouse is a data analysis technique. It can integrate all levels of data in enterprise database together and eventually form a data cube to show to end users. It can realize multi-dimensional analysis, and provide decision-making information for enterprise managers fast and intuitively. It becomes a powerful tool for decision-making. As the basic core of CRM, data warehouse will become more important in the field of business intelligence in future.
This paper studies the application of data warehouse technologies in enterprise CRM. According to the particular background of technologies application data warehouse with themes of customers, orders and others are built, using SQL Server 2000 to provide powerful storage and retrieval. This work takes open source OLAP engine Mondrian as the OLAP server o provide powerful multi-dimensional analysis, and employs OPENI as the front end of the analysis tools to provide multi-dimensional front-end display. Finally analytic CRM based on data warehouse technologies CRM. Multi-dimensional analysis customer value, customer classification and customer churn. It provides information to support decision-making for enterprise managers, and verify the validity of these models and methods in the application.
引文
[1]薛华成.管理信息系统.北京：清华大学出版社,1993.
[2]Han jiawei,Kamber Micheline.数据挖掘.北京：机械工业出版社,2001
[3]王珊.数据仓库技术与联机分析处理.北京：科学出版社,1998
[4]王娴,刘辉,倪远平.B/S与C/S体系结构的应用研究.信息技术.2006,6：54-58
[5]徐勇.分析型CRM中聚类算法的研究[D].兰州理工大学,2010
[6]刘建兰.数据挖掘技术在客户关系管理中的应用研究[D].南昌大学,2010.
[7]尚海昆K-means聚类算法的研究[D].华北电力大学(河北),2009
[8]李东,王民,陆亚娟.基于知识转移的客户关系管理(CRM)[J].管理世界,2008,(03).
[9]周赵宏,熊曙初.CRM中客户满意度分析[J].中国管理信息化(综合版),2007,(12).
[10]杨圣云,袁德辉,赖国明.一种新的聚类初始化方法.计算机应用与软件,2007,8(24)：51-52
[11]张艳芳,李晋宏,曹丹阳,魏金强.基于CF树的K-means聚类算法的改进.软件导刊,2005,15(5)：42-45
[12]毛韶阳,林肯立.优化K-means初始聚类中心研究.计算机工程与应用,2007,43(22)：179-181
[13]张彤.数据挖掘在客户关系管理中的应用.管理现代化,2003(4)：25-28
[14]刘小苏.基于Web面向中小企业的CRM系统的研究[D].西华大学,2010.
[15]施培蓓.数据挖掘技术中聚类算法的研究.无锡：江南大学硕士学位论文,2008
[16]Helmke, S,Dangelmaier, W,Uebel, M.F. CRM-systems as technology enabler for a customer-oriented knowledge management.Management of Engineering and Technology, 2001,9 (5):74-78.
[17]Yong Li,Zhi Xiao,Feng-Sheng Liu. Classification of clients in client relationship management (CRM) base on rough set theory.Machine Learning and Cybernetics,2003,17 (8):72-76.
[18]James,D. Better together marketing research and CRM.Marketing News,2002, vol.36 (no10):15-16.
[19]Salahi, A. Saffar, Y. Fakhry. Study and development of CRM information system for small and medium businesses.Information and Communication Technologies. From Theory to Applications,2004,11 (5):54-59.
[20]Newell. Customer Relationship Management in the New Era of Internet Marketing.New York:McGraw-Hill,1999,.
[21]Designing Enterprise Applications with the Java 2 Platform Enterprise Edition.Sun Microsystems, Inc,2000.
[22]A. Vakali,B. Catania,A. Maddalena. XML data store:emerging practices.IEEE Internet Computing,2005,9 (2):62-69.
[23]刘剑虹.企业CRM技术平台与业务模型的构建及其应用研究[D].中南大学,2002.
[24]王全,杨国梁.一种改进的K平均聚类算法.国外电子元器件,2008(9)：73-74
[25]杨圣云,袁德辉,赖国明.一种新的聚类初始化方法.计算机应用与软件,2007,8(24)：51-52
[26]陈尚松.基于J2EE的客户关系管理系统的设计与实现：[硕士学位论文).浙江：浙江大学,2008
[27]尹小勇.基于JAVA技术的B/S模式研究及应用[D].广西大学,2002.
[28]洪孟君.基于数据仓库的集团客户信息管理系统的设计与应用[D].武汉科技大学,2009.
[29]魏莉.基于数据仓库的电信经营分析与决策支持系统[D].湖南大学,2008.
[30]王炜,李建林.一种基于元数据仓库的元数据管理模型设计.计算技术与自动化,2005.
[31]何虎翼.聚类算法及其应用研究[D].上海交通大学,2007.
[32]Tae-Sun Chung,Hyoung-Joo Kim. Extracting indexing information from XML DTDs.Inormation Processing Letters,2002,(81):97-103
[33]P.Biron, A.Malhotra. XML Schema part 2:datatypes, W3C recommendation.
[34]http://www.w3.org/TR/2001/REC-XMLschema-2-20010502
[2]Han jiawei,Kamber Micheline.数据挖掘.北京：机械工业出版社,2001
[3]王珊.数据仓库技术与联机分析处理.北京：科学出版社,1998
[4]王娴,刘辉,倪远平.B/S与C/S体系结构的应用研究.信息技术.2006,6：54-58
[5]徐勇.分析型CRM中聚类算法的研究[D].兰州理工大学,2010
[6]刘建兰.数据挖掘技术在客户关系管理中的应用研究[D].南昌大学,2010.
[7]尚海昆K-means聚类算法的研究[D].华北电力大学(河北),2009
[8]李东,王民,陆亚娟.基于知识转移的客户关系管理(CRM)[J].管理世界,2008,(03).
[9]周赵宏,熊曙初.CRM中客户满意度分析[J].中国管理信息化(综合版),2007,(12).
[10]杨圣云,袁德辉,赖国明.一种新的聚类初始化方法.计算机应用与软件,2007,8(24)：51-52
[11]张艳芳,李晋宏,曹丹阳,魏金强.基于CF树的K-means聚类算法的改进.软件导刊,2005,15(5)：42-45
[12]毛韶阳,林肯立.优化K-means初始聚类中心研究.计算机工程与应用,2007,43(22)：179-181
[13]张彤.数据挖掘在客户关系管理中的应用.管理现代化,2003(4)：25-28
[14]刘小苏.基于Web面向中小企业的CRM系统的研究[D].西华大学,2010.
[15]施培蓓.数据挖掘技术中聚类算法的研究.无锡：江南大学硕士学位论文,2008
[16]Helmke, S,Dangelmaier, W,Uebel, M.F. CRM-systems as technology enabler for a customer-oriented knowledge management.Management of Engineering and Technology, 2001,9 (5):74-78.
[17]Yong Li,Zhi Xiao,Feng-Sheng Liu. Classification of clients in client relationship management (CRM) base on rough set theory.Machine Learning and Cybernetics,2003,17 (8):72-76.
[18]James,D. Better together marketing research and CRM.Marketing News,2002, vol.36 (no10):15-16.
[19]Salahi, A. Saffar, Y. Fakhry. Study and development of CRM information system for small and medium businesses.Information and Communication Technologies. From Theory to Applications,2004,11 (5):54-59.
[20]Newell. Customer Relationship Management in the New Era of Internet Marketing.New York:McGraw-Hill,1999,.
[21]Designing Enterprise Applications with the Java 2 Platform Enterprise Edition.Sun Microsystems, Inc,2000.
[22]A. Vakali,B. Catania,A. Maddalena. XML data store:emerging practices.IEEE Internet Computing,2005,9 (2):62-69.
[23]刘剑虹.企业CRM技术平台与业务模型的构建及其应用研究[D].中南大学,2002.
[24]王全,杨国梁.一种改进的K平均聚类算法.国外电子元器件,2008(9)：73-74
[25]杨圣云,袁德辉,赖国明.一种新的聚类初始化方法.计算机应用与软件,2007,8(24)：51-52
[26]陈尚松.基于J2EE的客户关系管理系统的设计与实现：[硕士学位论文).浙江：浙江大学,2008
[27]尹小勇.基于JAVA技术的B/S模式研究及应用[D].广西大学,2002.
[28]洪孟君.基于数据仓库的集团客户信息管理系统的设计与应用[D].武汉科技大学,2009.
[29]魏莉.基于数据仓库的电信经营分析与决策支持系统[D].湖南大学,2008.
[30]王炜,李建林.一种基于元数据仓库的元数据管理模型设计.计算技术与自动化,2005.
[31]何虎翼.聚类算法及其应用研究[D].上海交通大学,2007.
[32]Tae-Sun Chung,Hyoung-Joo Kim. Extracting indexing information from XML DTDs.Inormation Processing Letters,2002,(81):97-103
[33]P.Biron, A.Malhotra. XML Schema part 2:datatypes, W3C recommendation.
[34]http://www.w3.org/TR/2001/REC-XMLschema-2-20010502