基于数据挖掘的移动资费体系研究
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摘要
随着电信行业的改革重组和全业务运营的综合竞争,通信企业之间的竞争日趋激烈,国内、国际电信业的竞争态势,对电信运营企业的服务意识、服务内容、服务方式、服务质量以及经营管理水平等均提出了严峻的挑战,客户作为通信企业生存和发展的最重要的资源成为争夺的焦点。客户对服务的要求越来越高,不同的客户群体将产生不同的需求。一成不变的市场策略不再能满足多样化、个性化发展的客户需求。
资费套餐是电信行业的重要产品,是以满足市场需要,获得最佳经济利益为目的的组合营销方式,即将各种业务进行组合,以满足不同消费群体的目标客户需求,同时优惠的资费使用户得到了切实的利益,提高了业务的吸引力,很大程度上提高了用户的满意度和忠诚度,增强了企业在新增市场的竞争力和存量市场的用户粘性,同时也促进了各种业务在组合中增值,增强了企业的盈利能力。资费套餐作为新的竞争方式,已经成为运营商主要的竞争手段之一。
本文的研究建立在某省移动经营分析系统(BASS,Business Analysis Supporting System)用户的真实数据基础上,根据客户的自然属性、社会属性、通信属性、消费习惯、消费行为等特征,采用数据挖掘中的聚类方法,对客户进行需求分群,建立客户消费需求细分模型,并结合资费套餐设计原则进行移动资费套餐的研究,设计出一整套全新的移动资费体系,为移动运营企业进行套餐设计提供了科学的方法支撑,在提高客户满意度、移动运营商的竞争力和经营效益的同时,也对其他行业的资费套餐设计有一定的借鉴价值。
With the reform and reorganization of the telecommunications industry and comprehensive competitive full-service operations, communication enterprises increase fierce competition. The competitive situation of domestic and international telecommunications industry, telecom companies on the sense of service, service content, service mode, service quality and management level all put forward a serious challenge. Customer is the most important resource of communications enterprise survival and development, it becomes the focus of contention, Customer service have become increasingly demanding, different customer segments will have different needs. Static market strategies can no longer meet the diversified development of individualized customer needs.
Tariff package is the important product the telecommunications industry, meets the market needs, gets the best combination of economic benefits for the purpose of marketing, it will be combined a variety of services to meet different needs of target consumer groups, while preferential tariff allows users to have tangible benefits and improves the attractiveness of the business, largely improves customer satisfaction and loyalty, enhances the enterprise's competitiveness in the new market, and the stock market, the user stickiness, and also promotes various kinds of business in the portfolio value and enhances profitability of the enterprises. Tariff packages as a new form of competition had become a major competitive carrier one of the means.
This research establishes mobile operators in the province BASS (Business Analysis Supporting System) user's real data based on the customer's natural attributes, social attributes, communications, property, consumer habits, consumer behavior and other characteristics. It uses data mining clustering method to group customers needs, then builds customer segmentation model of consumer demand, combines mobile tariff packages design principles to study tariff packages, then we design a set of new mobile tariff system , provide a scientific method support for mobile operators and enterprises package design, with improving customer satisfaction, mobile operators, competitiveness and operational effectiveness, while for other sectors also have a certain tariff packages designed to reference value.
资费套餐是电信行业的重要产品,是以满足市场需要,获得最佳经济利益为目的的组合营销方式,即将各种业务进行组合,以满足不同消费群体的目标客户需求,同时优惠的资费使用户得到了切实的利益,提高了业务的吸引力,很大程度上提高了用户的满意度和忠诚度,增强了企业在新增市场的竞争力和存量市场的用户粘性,同时也促进了各种业务在组合中增值,增强了企业的盈利能力。资费套餐作为新的竞争方式,已经成为运营商主要的竞争手段之一。
本文的研究建立在某省移动经营分析系统(BASS,Business Analysis Supporting System)用户的真实数据基础上,根据客户的自然属性、社会属性、通信属性、消费习惯、消费行为等特征,采用数据挖掘中的聚类方法,对客户进行需求分群,建立客户消费需求细分模型,并结合资费套餐设计原则进行移动资费套餐的研究,设计出一整套全新的移动资费体系,为移动运营企业进行套餐设计提供了科学的方法支撑,在提高客户满意度、移动运营商的竞争力和经营效益的同时,也对其他行业的资费套餐设计有一定的借鉴价值。
With the reform and reorganization of the telecommunications industry and comprehensive competitive full-service operations, communication enterprises increase fierce competition. The competitive situation of domestic and international telecommunications industry, telecom companies on the sense of service, service content, service mode, service quality and management level all put forward a serious challenge. Customer is the most important resource of communications enterprise survival and development, it becomes the focus of contention, Customer service have become increasingly demanding, different customer segments will have different needs. Static market strategies can no longer meet the diversified development of individualized customer needs.
Tariff package is the important product the telecommunications industry, meets the market needs, gets the best combination of economic benefits for the purpose of marketing, it will be combined a variety of services to meet different needs of target consumer groups, while preferential tariff allows users to have tangible benefits and improves the attractiveness of the business, largely improves customer satisfaction and loyalty, enhances the enterprise's competitiveness in the new market, and the stock market, the user stickiness, and also promotes various kinds of business in the portfolio value and enhances profitability of the enterprises. Tariff packages as a new form of competition had become a major competitive carrier one of the means.
This research establishes mobile operators in the province BASS (Business Analysis Supporting System) user's real data based on the customer's natural attributes, social attributes, communications, property, consumer habits, consumer behavior and other characteristics. It uses data mining clustering method to group customers needs, then builds customer segmentation model of consumer demand, combines mobile tariff packages design principles to study tariff packages, then we design a set of new mobile tariff system , provide a scientific method support for mobile operators and enterprises package design, with improving customer satisfaction, mobile operators, competitiveness and operational effectiveness, while for other sectors also have a certain tariff packages designed to reference value.
引文
[1]吕廷杰,尹涛,王琦.客户关系管理与主题分析[M].北京:人民邮电出版社,2002.
[2]迈克尔·J.A.贝里,戈登·S.利诺夫(美).数据挖掘:客户关系管理的科学与艺术.北京:中国财政经济出版社,2004.
[3]张光建,黄贤英.基于最小聚类单元的聚类算法研究及其在CRM中的应用[J].计算机科学,2006,33(7):188-190.
[4]范英,张忠健.聚类方法在通信行业客户细分中的应用[J].计算机工程,2004-12.
[5]郝先臣等.数据挖掘工具和应用中的问题.东北大学学报,2000 4:183-187.
[6]李宝东.数据挖掘在客户关系管理(CRM)中的应用.计算机应用研究,2002,(10):71-74.
[7]周锦文.数据仓库和数据挖掘技术在移动业务中的应用:[硕士学位论文].长沙:中南大学,2003.
[8]孙孝萍.基于聚类分析的数据挖掘算法研究.西南石油学院硕士论文.2002,3:26-43.
[9]廖里,余英泽等.数据挖掘和数据仓库及其在电信业中的应用.重庆邮电学院学报,2004.4:31-34.
[10]eTOM模型http://publish.it168.com/2004/1028/20041028000701.shtml 2004.10.8
[11]杨瑞祯,黄传武.电信市场营销基本理论与实务北京邮电大学出版社2003年7月
[12]齐佳音,舒华英等 移动通信业务套餐设计原则探讨世界电信2004(7)
[13]姜正新 电信资费模式研究经济理论与经济管理2005(11)
[14]张云华 移动通信资费模式与价格策略研究[学位论文]北京邮电大学
[15]彭云飞,马超群 电信业务定价决策理论研究中国管理科学2006(6)
[16]武超 电信领域优惠模型的研究[学位论文]北京邮电大学
[17]王靖林 电信产品管理系统的研究与设计[学位论文]北京邮电大学
[18]蔡自,John Durkin,龚涛 高级专家系统:原理、设计与应用科学出版社2004
[19]TMForum网站http://www.www.tmforum.org
[20]中国移动通信集团公司网站http://www.chinamobile.com
[21]中国联合通信有限公司网站http://www.chinaunicom.eom.en
[22]邹兰,张泽伟.中国电话用户数突破6亿手机用户达到3.1亿.人民邮电报,2004.7
[23]毕波.八大趋势看2006年电信运营.通信世界,2006.
[24]丁秋林,力士奇.客户关系管理[M).北京:清华大学出版社,2002.2
[25]董金祥等编著.客户关系管理.杭州:浙江大学出版社,2002.
[26]杨东龙,客户关系管理.北京:中国经济出版社,2002.
[27]汤小文,蔡庆生.数据挖掘在电信业中的应用.计算机工程,2004.6
[28]李连祥.中国电信全国计费结算中心BI系统建设.通信世界,2003.9
[29]郭道宁,舒华英.数据挖掘在电信运营市场决策支持中的应用.北京邮电大学学报,2004.6
[30]赵宏波,孟雅玲.数据挖掘在电信客户关系管理中的应用.电信技术,2001.12
[31]王琳.数据挖掘技术在通信规划和预测中的应用.邮电规划,2004.2
[32]耿庆鹏.利用数据挖掘技术实现对电信行业用户欺诈行为的预测.电信快报,2003.10
[33]刘世平,姚玉辉博士.数据挖掘工具的评判.数字财富,2003.6
[34]李德仁,王树良等.论空间数据挖掘和知识发现.武汉大学学报(信息科学版),2001.9
[35]张国重,基于数据库和数据挖掘技术的客户关系管理.现代计算机.2002.10.
[36]冯萍,宣慧玉.数据挖掘技术及其在营销中的应用.北京轻工业学院学报.2001.19
[37]陈明亮.客户价值细分与保持策略研究.成组技术与生产现代化.2001.4
[38]张国方,金国栋.客户细分理论及应用策略研究华中科技大学学报,社会科学版.2003.3
[39]陈明亮.客户生命周期模式研究.浙江大学学报(社会科学版).2002.32
[40]匡奕球.基于生命周期的客户终身价值分析.四川工业学院学报.2003.1
[41]王松,我国通信产品资费套餐涉及之我见,通信世界,2005,http://tech.sina.eom.2005-08-15/1731693690.shtml
[42]陈俊瑞,如何构建合理的资费套餐体系,2005,http://www.cnii.com.cn20050508/ea307656.html
[43]Miehellema,资费套餐设计的艺术,2005,http://www.3719.en
[44]段云峰,吴唯宁,中国的移动经营分析系统介绍,电信技术,2001
[45]Jiawei Han and Micheline Kamber,Data Mining:Concepts and Techniques,2nd edition,Morgan Kaufmann,2006.
[46]SPSS.CRISP-DM:Step-by-step Data Mining Guide[EB/OL].http://www.crisp-dm.org /CRISPWP-O8OO.pdf.2000-08-15.
[47]Alex Berson,Stephen Smith,Kurt Thearling.Data Mining Applieation for CMR.北京:人民邮电出版社,2001.25.
[48]LouiSE.Boone,DavidL.Kurtz(美)著.赵银德译.当代市场营销学.北京:机械工业出版社,2003
[49]HUNG S-Y,YEN DC,WANG H-Y.Applying data mining to telecom churn management[J].Expert Systems with Applications,2006,31(3):515-524.
[50]KalfmaIl L,Rousseeuw P J.Finding Groups in Data:An Introduction toClusterAnalysis[M].NewYork:JohnWiley&Sons.1990.
[51]Dean W.Abbot,1.Philip Matkovsky,and John F.Elder Ⅳ,An Evaluation of High-end DataMining Tools for Fraud Detection,1998 IEEE International Conference on Systems,Man,and Cybernetics,San Diego,CA,October 12-14,2001.
[52]TMForum GB921D_Release6-0--v61.eTOM AddendumD:Proeess Decom Positions and DeseriPtions Release 6.0
[53]Carrie M.Heilman,Douglas Bowman.Segmenting Consumers Using Multiple-Category Purchase Data[J].International Journal of Research in Marketing,2002,19(3):225-252.
[54]T.K.Ho,J.J.Hull,S.N.Srihari.Decision Combination in Multiple Classifier Systems[J].IEEE Trans.Pattern Anal.Mach.Intell,1994,16(1):66-75.
[55]StanleyA.Broo.Customer Relationship Management:A Strategie Imperative inthe World of EBusiness.John Wiley&Sons,2000:6
[56]DarrellK.Rigby,Management tools 2001 global results:Annual survey of senior exeeutives.BAI&NCOMPANY Ine Researeh Report,2002.1-4
[57]Gordon5.Linoff,Mi.haelJ.A.Berry.Mining the Web:Transforming Customer Dataintion Customer Value.John Wiley&sons,Ine,2004.3
[58]George M.Marakas.Modern Data Warehousing,Mining,and Visualization.清华大学出版社,2004
[2]迈克尔·J.A.贝里,戈登·S.利诺夫(美).数据挖掘:客户关系管理的科学与艺术.北京:中国财政经济出版社,2004.
[3]张光建,黄贤英.基于最小聚类单元的聚类算法研究及其在CRM中的应用[J].计算机科学,2006,33(7):188-190.
[4]范英,张忠健.聚类方法在通信行业客户细分中的应用[J].计算机工程,2004-12.
[5]郝先臣等.数据挖掘工具和应用中的问题.东北大学学报,2000 4:183-187.
[6]李宝东.数据挖掘在客户关系管理(CRM)中的应用.计算机应用研究,2002,(10):71-74.
[7]周锦文.数据仓库和数据挖掘技术在移动业务中的应用:[硕士学位论文].长沙:中南大学,2003.
[8]孙孝萍.基于聚类分析的数据挖掘算法研究.西南石油学院硕士论文.2002,3:26-43.
[9]廖里,余英泽等.数据挖掘和数据仓库及其在电信业中的应用.重庆邮电学院学报,2004.4:31-34.
[10]eTOM模型http://publish.it168.com/2004/1028/20041028000701.shtml 2004.10.8
[11]杨瑞祯,黄传武.电信市场营销基本理论与实务北京邮电大学出版社2003年7月
[12]齐佳音,舒华英等 移动通信业务套餐设计原则探讨世界电信2004(7)
[13]姜正新 电信资费模式研究经济理论与经济管理2005(11)
[14]张云华 移动通信资费模式与价格策略研究[学位论文]北京邮电大学
[15]彭云飞,马超群 电信业务定价决策理论研究中国管理科学2006(6)
[16]武超 电信领域优惠模型的研究[学位论文]北京邮电大学
[17]王靖林 电信产品管理系统的研究与设计[学位论文]北京邮电大学
[18]蔡自,John Durkin,龚涛 高级专家系统:原理、设计与应用科学出版社2004
[19]TMForum网站http://www.www.tmforum.org
[20]中国移动通信集团公司网站http://www.chinamobile.com
[21]中国联合通信有限公司网站http://www.chinaunicom.eom.en
[22]邹兰,张泽伟.中国电话用户数突破6亿手机用户达到3.1亿.人民邮电报,2004.7
[23]毕波.八大趋势看2006年电信运营.通信世界,2006.
[24]丁秋林,力士奇.客户关系管理[M).北京:清华大学出版社,2002.2
[25]董金祥等编著.客户关系管理.杭州:浙江大学出版社,2002.
[26]杨东龙,客户关系管理.北京:中国经济出版社,2002.
[27]汤小文,蔡庆生.数据挖掘在电信业中的应用.计算机工程,2004.6
[28]李连祥.中国电信全国计费结算中心BI系统建设.通信世界,2003.9
[29]郭道宁,舒华英.数据挖掘在电信运营市场决策支持中的应用.北京邮电大学学报,2004.6
[30]赵宏波,孟雅玲.数据挖掘在电信客户关系管理中的应用.电信技术,2001.12
[31]王琳.数据挖掘技术在通信规划和预测中的应用.邮电规划,2004.2
[32]耿庆鹏.利用数据挖掘技术实现对电信行业用户欺诈行为的预测.电信快报,2003.10
[33]刘世平,姚玉辉博士.数据挖掘工具的评判.数字财富,2003.6
[34]李德仁,王树良等.论空间数据挖掘和知识发现.武汉大学学报(信息科学版),2001.9
[35]张国重,基于数据库和数据挖掘技术的客户关系管理.现代计算机.2002.10.
[36]冯萍,宣慧玉.数据挖掘技术及其在营销中的应用.北京轻工业学院学报.2001.19
[37]陈明亮.客户价值细分与保持策略研究.成组技术与生产现代化.2001.4
[38]张国方,金国栋.客户细分理论及应用策略研究华中科技大学学报,社会科学版.2003.3
[39]陈明亮.客户生命周期模式研究.浙江大学学报(社会科学版).2002.32
[40]匡奕球.基于生命周期的客户终身价值分析.四川工业学院学报.2003.1
[41]王松,我国通信产品资费套餐涉及之我见,通信世界,2005,http://tech.sina.eom.2005-08-15/1731693690.shtml
[42]陈俊瑞,如何构建合理的资费套餐体系,2005,http://www.cnii.com.cn20050508/ea307656.html
[43]Miehellema,资费套餐设计的艺术,2005,http://www.3719.en
[44]段云峰,吴唯宁,中国的移动经营分析系统介绍,电信技术,2001
[45]Jiawei Han and Micheline Kamber,Data Mining:Concepts and Techniques,2nd edition,Morgan Kaufmann,2006.
[46]SPSS.CRISP-DM:Step-by-step Data Mining Guide[EB/OL].http://www.crisp-dm.org /CRISPWP-O8OO.pdf.2000-08-15.
[47]Alex Berson,Stephen Smith,Kurt Thearling.Data Mining Applieation for CMR.北京:人民邮电出版社,2001.25.
[48]LouiSE.Boone,DavidL.Kurtz(美)著.赵银德译.当代市场营销学.北京:机械工业出版社,2003
[49]HUNG S-Y,YEN DC,WANG H-Y.Applying data mining to telecom churn management[J].Expert Systems with Applications,2006,31(3):515-524.
[50]KalfmaIl L,Rousseeuw P J.Finding Groups in Data:An Introduction toClusterAnalysis[M].NewYork:JohnWiley&Sons.1990.
[51]Dean W.Abbot,1.Philip Matkovsky,and John F.Elder Ⅳ,An Evaluation of High-end DataMining Tools for Fraud Detection,1998 IEEE International Conference on Systems,Man,and Cybernetics,San Diego,CA,October 12-14,2001.
[52]TMForum GB921D_Release6-0--v61.eTOM AddendumD:Proeess Decom Positions and DeseriPtions Release 6.0
[53]Carrie M.Heilman,Douglas Bowman.Segmenting Consumers Using Multiple-Category Purchase Data[J].International Journal of Research in Marketing,2002,19(3):225-252.
[54]T.K.Ho,J.J.Hull,S.N.Srihari.Decision Combination in Multiple Classifier Systems[J].IEEE Trans.Pattern Anal.Mach.Intell,1994,16(1):66-75.
[55]StanleyA.Broo.Customer Relationship Management:A Strategie Imperative inthe World of EBusiness.John Wiley&Sons,2000:6
[56]DarrellK.Rigby,Management tools 2001 global results:Annual survey of senior exeeutives.BAI&NCOMPANY Ine Researeh Report,2002.1-4
[57]Gordon5.Linoff,Mi.haelJ.A.Berry.Mining the Web:Transforming Customer Dataintion Customer Value.John Wiley&sons,Ine,2004.3
[58]George M.Marakas.Modern Data Warehousing,Mining,and Visualization.清华大学出版社,2004