Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.


Top researchers from over 74 countries worldwide have trusted us because of quality publications.

United States of America
United Kingdom
Saudi Arabia
Predicting e-Customer behavior in B2C Relationships for CLV model
Kaveh Ahmadi
Pages - 128 - 138     |    Revised - 01-09-2011     |    Published - 05-10-2011
Volume - 2   Issue - 3    |    Publication Date - September / October 2011  Table of Contents
Customer Lifetime Value (CLV), e-Commerce Relationships, Net Present Value (NPV), customer's behavior, Customer Segmentation
E-Commerce sales have demonstrated an amazing growth in the last few years. And it is thus clear that the web is becoming an increasingly important channel and companies should strive for a successful web site. In this completion knowing e-customer and predicting his behavior is very important. In this paper we describe e-customer behavior in B2C relationships and then according to this behavior a new model for evaluating e-customer in B2C e-commerce relationships will be described. The most important thing in our e-CLV (Electronic Customer Lifetime Value) model is considering market\'s risks that are affecting customer cash flow in future. A lot of CLV models are based on simple NPV (simple net present value). However simple NPV can assess a good value for CLV, but simple NPV ignores two important aspects of B2C e-relationship which are market risks and big amount of customer data in e-commerce context. Therefore, simple NPV isn\'t enough for assessing e-CLV in high risk B2C markets. Instead of NPV, real option analyses could lead us to a better estimation for future cash flow of customers. With real option analyses, we predict all the future states with probability of each of them. And then calculate the more accurate of future customer cash flow. In this paper after a brief history of CLV, we explain customer behavior in B2C markets especially for e-retailers. Then with using real option analyses, we introduce our CLV model. Two extended examples explain our model and introduce the steps in finding CLV of customer in a B2C relationship.
1 Google Scholar 
2 CiteSeerX 
3 Scribd 
4 SlideShare 
5 PdfSR 
2 P.Paauwe, P. v. Putten and M. v.Wezel. "DTMC: An Actionable e-Customer Lifetime Value Model Based on Markov Chains and Decision Trees" presented at the ICEC 07 conference, Minnesota, USA, 2007.
3 E. C. Bursk, “View your customers as investments” in Proc. Harvard Business Review, 1966, pp. 91-94.
4 B.B. Jackson, Winning and Keeping Industrial Customers, Lexington Books, D.C. Heath &Company, 1985, pp. 30-85.
5 R.F.Dwyer, "Customer lifetime valuation to support marketing decision making" Journal of Direct Marketing, 1989 (reprinted Vol. 11, pp. 6-13, 1997).
6 P.D.Berger, and N.I. Nasr, “Customer lifetime value: marketing models and applications” Journal of Interactive Marketing, Vol.12, pp. 17-30, 1998.
7 P. E. Pfeifer and R. L. Carraway. “Modeling customer relationships as Markov chains” Journal of interactive marketing, Vol. 14, pp. 43–55, 2000.
8 F.A.Jacobs, W. Johnston, and N. Kotchetova, “Customer profitability: prospective vs. retrospective approaches in a business-to-business setting” Journal of Industrial Marketing Management, Vol. 30,pp. 353-363, 2001.
9 W.J. Reinartz, and V. Kumar, “The impact of customer relationship characteristics on profitable lifetime duration” Journal of Marketing, Vol. 67, pp. 77-99, 2003.
10 R.A. Brealey and S.C.Myers, Principles of Corporate Finance, New York: McGraw-Hill Press, 2005, pp. 121-130.
11 M. Adams,”Real options and customer management in the financial services sector” Journal of Strategic Marketing, Vol. 12, pp. 3-11, 2004.
12 E. Roemer, “A typology of customer lifetime values buyer–seller relationships” Journal of Strategic Marketing, Vol. 15, pp. 441-457, 2007.
13 K. Ahmadi, H. Taherdoost, “A new model for evaluating Customer Lifetime Value in High Risk Markets” in Proc. International Conference on Social Science and Humanity (ICSSH 2011),2011, pp. 309-312.
14 D.G.Schmittlein, and R.A. Peterson “Customer Base Analysis: An Industrial Purchase Process Application” Journal of Marketing Science, Vol. 13, pp. 41-67,(Winter) 1994.
15 P.S. FADER, B. HARDIE, and K. LEE, " RFM and CLV: Using Iso-Value Curves for Customer Base Analysis" Journal of Marketing Research, Vol. XLII, pp. 415–430, Nov. 2005.
16 Gupta, Sunil and Lehmann, "Customer Lifetime Value and Firm Valuation" Journal of Relationship Marketing, Vol. 5, I. 2, pp. 87-110, 2006.
17 N. B. Baesens and C.Croux, "A modified Pareto/NBD approach for predicting customer lifetime value", journal of Expert Systems with Applications ,Vol. 36, I. 2, Part 1, pp. 2062- 2071, March, 2009.
18 T. Copeland and V. Antikarov, Real Options: A Practitioner’s Guide, London: Texere Press, 2006, pp. 10-64.
19 M. Amram and N. Kulatilaka Real Options: Managing Strategic Investment in an Uncertain World, Boston, MA: Harvard Business School Press, 1999, pp.103-150.
20 A. Micalizzi and L. Trigeorgis Real Options and Business Strategy, London: Risk Books, 2008, pp. 40-80.
21 R. Adner and D.A.Levinthal, "What is not a real option: identifying boundaries for the application of real options to business strategy" Journal of Academy of Management Review, Vol. 29, pp. 74-85, 2004.
22 S.L. chan, W.H.IP, V. Cho, "A model for predicting customer value from perspectives of product attractiveness and marketing strategy", International Journal of Expert Systems with Application, Vol. 37, pp. 1207-1215, 2010.
Mr. Kaveh Ahmadi
Islamic Azad University, Islamshahr Branch - Iran