Modeling Repeat Purchases in the Internet when RFM Captures Past Influence of Marketing
Predicting online customer repeat purchase behavior by accounting for the marketing-mix plays an important role in a variety of empirical studies regarding individual customer relationship management. A number of sophisticated models have been developed for different forecasting purposes based on a – mostly linear – combination of purchase history, so called Recency-Frequency-Monetary Value (RFM)-variables and marketing variables. However, these studies focus on a high predictive validity rather than ensuring that their proposed models capture the original effects of marketing activities. Thus, they ignore an explicit relationship between the purchase history and marketing which leads to biased estimates in case these variables are correlated. This study develops a modeling framework for the prediction of repeat purchases that adequately combines purchase history data and marketing-mix information in order to determine the original impact of marketing. More specifically, we postulate that RFM already captures the effects of past marketing activities and the original marketing impact is represented by temporal changes from the purchase process. Our analysis highlights and confirms the importance of adequately modeling the relationship between RFM and marketing. In addition, the results show superiority of the proposed model compared to a model with a linear combination of RFM and marketing variables.
|Date of creation:||25 Oct 2011|
|Date of revision:|
|Contact details of provider:|| Postal: Düsternbrooker Weg 120, 24105 Kiel / Neuer Jungfernstieg 21, 20354 Hamburg|
Phone: +49 431 8814-1
Fax: +49 431 8814-520
Web page: http://www.econstor.eu/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jie Zhang & Lakshman Krishnamurthi, 2004. "Customizing Promotions in Online Stores," Marketing Science, INFORMS, vol. 23(4), pages 561-578, June.
- Puhani, Patrick A, 2000. " The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
- Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
- Heckman, James, 2013.
"Sample selection bias as a specification error,"
Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
- Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
- Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
- Romana Khan & Michael Lewis & Vishal Singh, 2009. "Dynamic Customer Management and the Value of One-to-One Marketing," Marketing Science, INFORMS, vol. 28(6), pages 1063-1079, 11-12.
- Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
- Sharad Borle & Siddharth S. Singh & Dipak C. Jain, 2008. "Customer Lifetime Value Measurement," Management Science, INFORMS, vol. 54(1), pages 100-112, January.
- Roland T. Rust & Peter C. Verhoef, 2005. "Optimizing the Marketing Interventions Mix in Intermediate-Term CRM," Marketing Science, INFORMS, vol. 24(3), pages 477-489, December.
- Van den Poel, Dirk & Buckinx, Wouter, 2005.
"Predicting online-purchasing behaviour,"
European Journal of Operational Research,
Elsevier, vol. 166(2), pages 557-575, October.
- W.R Buckinx & D. Van Den Poel, 2003. "Predicting Online Purchasing Behavior," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/195, Ghent University, Faculty of Economics and Business Administration.
- Joel H. Steckel & Wilfried R. Vanhonacker, 1993. "Cross-Validating Regression Models in Marketing Research," Marketing Science, INFORMS, vol. 12(4), pages 415-427.
- David C. Schmittlein & Robert A. Peterson, 1994. "Customer Base Analysis: An Industrial Purchase Process Application," Marketing Science, INFORMS, vol. 13(1), pages 41-67.
- G. S. Maddala, 1987. "Limited Dependent Variable Models Using Panel Data," Journal of Human Resources, University of Wisconsin Press, vol. 22(3), pages 307-338.
When requesting a correction, please mention this item's handle: RePEc:zbw:esprep:50730. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics)
If references are entirely missing, you can add them using this form.