Abstract
e-Commerce companies acknowledge that customers are their most important asset and that it is imperative to estimate the potential value of this asset.
In conventional marketing, one of the widely accepted methods for evaluating customer value uses models known as Customer Lifetime Value (CLV). However, these existing models suffer from two major shortcomings: They either do not take into account significant attributes of customer behavior unique to e-Commerce, or they do not provide a method for generating specific models from the large body of relevant historical data that can be easily collected in e-Commerce sites.
This paper describes a general modeling approach, based on Markov Chain Models, for calculating customer value in the e-Commerce domain. This approach extends existing CLV models, by taking into account a new set of variables required for evaluating customers value in an e-Commerce environment. In addition, we describe how data-mining algorithms can aid in deriving such a model, thereby taking advantage of the historical customer data available in such environments. We then present an application of this modeling approach—the creation of a model for online auctions—one of the fastest-growing and most lucrative types of e-Commerce. The article also describes a case study, which demonstrates how our model provides more accurate predictions than existing conventional CLV models regarding the future income generated by customers.
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References
Baesens B, Viaene S, Van den Poel D, Vanthienen J, Dedene G. Bayesian neural networking learning for repeat purchase modeling in direct marketing. European Journal of Operational Research, 2002:191–211.
Berger PD, Nasr NI. Customer lifetime value: Marketing models and applications. Journal of Interactive Marketing 1998:17–30.
“English Auction” definition from URL: http://www.gametheory.net/Dictionary/Auctions/EnglishAuction.html
Gupta, S., Lehmann, DR, and Stuart, JA. “Valuing Vustomers.” Working E-commerce.
Hoekstra JC, Huizingh EKRE. The lifetime value concept in customers-based marketing. Journal of Marketing Focused Management, 1999:257–274.
Kaymak U. Fuzzy target selection using RFM variables, In: Proceedings of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, Canada, 1038–1043;2001.
Kim Y, Street WN, Russel GJ, Menczer F. Customer targeting: A neural network approach guided by genetic algorithms, 2001.
Menasce DA, Almeida VAF. Scaling for E-Business, Prentice Hall, 2000, ISBN 0-13-086328-9.
Mulhern Francis J. Customer profitability analysis: Measurement, concentration, and research direction. Journal of Interactive Marketing 1999:25–40.
Pfeifer PE, Carraway RL. Modeling customers relationship as markov chains, Journal of Interactive Marketing, Spring 2000.
Russell SJ, Norvig P. Artificial intelligence: A Modern Approach. Prentice Hall, 2nd edn., ISBN: 0137903952, 1995.
Rust RT, Zeithaml VA, Lemon KN. Driving Customer Equity: How Customers Lifetime Value Is Reshaping Corporate Strategy, The Free Press, 2000.
StatSoft Inc., 1984–2003 URL: http://www.statsoftinc.com/textbook/stathom.html
Stahl H ., Matzler K, Hinterhuber HH. Linking customer lifetime value with shareholder value. Industrial Marketing Management, 2002:1–13
Viaene S, Baesens B, Van Gestel T, Suykens JAK, Van den Poel D, Vanthienen J, De Moor B, Dedene G. Knowledge discovery using least squares support vector machine classifiers: A direct marketing case. Management Science, 2001.
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Opher Etzion is a research staff member and the manager of the active management technology group in IBM Research Laboratory in Haifa, Israel, and a visiting research scientist at the Technion—Israel Institute of Technology. He received BA degree in Philosophy from Tel-Aviv University and Ph.D. degree in Computer Science from Temple University, Prior to joining IBM in 1997, he has been a faculty member at the Technion, where he has served as the founding head of the information systems engineering area and graduate program. Prior to his graduate studies, he held professional and managerial positions in industry and in the Israel Air-Force, receiving the air-force highest award in 1982. His research interests include active technology (active databases and beyond), temporal databases, middleware systems and rule-base systems. He is a member of the editorial board of the IIE Transactions Journal, was a guest editor in the Journal of Intelligent Information Systems in 1994, and a guest editor in the International Journal of Cooperative Information Systems (2001). He served as a coordinating organizer of the Dagstuhl seminar on Temporal databases in 1997, has been the coeditor of the book “Temporal Databases—Research and Practice” published by Springer-Verlag, in 2000 he has been program chair of CoopIS'2000, and demo and panel chair of VLDB'2000. He also served in many conferences program committees (e.g. VLDB, ICDE, ER) as well as national committees and has been program and general chair in the NGITS workshop series.
Amit Fisher is a research staff member in the active management technology group in IBM Research Laboratory in Haifa, Israel. He received B.Sc. degree in Industrial Engineering and Management and M.Sc. degree in Information System Engineering from the Technion—Israel institute of Technology.
Prior to joining IBM research, Amit held a professional position in Israel Air-Force. He's research interests include Customer Behavior Analysis, CRM, Data Mining and Business Process Management.
Segev Wasserkrug is a research staff member at IBM's Haifa Research lab (HRL). He has a M.Sc. in computer science, in the area of neural networks. In addition, he has significant experience in modeling of various types, automatic model derivation, and optimization, gained from leading the development of a technology in HRL that deals with optimization of an IT infrastructure according to business objectives. He is also currently studying towards a Ph.D. in information systems at the Technion, Israel Institute of Technology, in the area of uncertainty handling, based on Bayesian network techniques
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Etzion, O., Fisher, A. & Wasserkrug, S. e-CLV: A Modeling Approach for Customer Lifetime Evaluation in e-Commerce Domains, with an Application and Case Study for Online Auction. Inf Syst Front 7, 421–434 (2005). https://doi.org/10.1007/s10796-005-4812-6
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DOI: https://doi.org/10.1007/s10796-005-4812-6