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Choice Models and Customer Relationship Management

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Author Info

  • Wagner Kamakura

    ()

  • Carl Mela
  • Asim Ansari
  • Anand Bodapati
  • Pete Fader
  • Raghuram Iyengar
  • Prasad Naik
  • Scott Neslin
  • Baohong Sun
  • Peter Verhoef
  • Michel Wedel
  • Ron Wilcox

Abstract

Customer relationship management (CRM) typically involves tracking individual customer behavior over time, and using this knowledge to configure solutions precisely tailored to the customers' and vendors' needs. In the context of choice, this implies designing longitudinal models of choice over the breadth of the firm's products and using them prescriptively to increase the revenues from customers over their lifecycle. Several factors have recently contributed to the rise in the use of CRM in the marketplace A shift in focus in many organizations, towards increasing the share of requirements among their current customers rather than fighting for new customers. An explosion in data acquired about customers, through the integration of internal databases and acquisition of external syndicated data. Computing power is increasing exponentially. Software and tools are being developed to exploit these data and computers, bringing the analytical tools to the decision maker, rather than restricting their access to analysts. In spite of this growth in marketing practice, CRM research in academia remains nascent. This paper provides a framework for CRM research and describes recent advances as well as key research opportunities. See http://faculty.fuqua.duke.edu/~mela for a more complete version of this paper Copyright Springer Science + Business Media, Inc. 2005

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Bibliographic Info

Article provided by Springer in its journal Marketing Letters.

Volume (Year): 16 (2005)
Issue (Month): 3 (December)
Pages: 279-291

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Handle: RePEc:kap:mktlet:v:16:y:2005:i:3:p:279-291

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Web page: http://www.springerlink.com/link.asp?id=100312

Related research

Keywords: customer relationship management; direct marketing;

References

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  1. Prasad A. Naik & Chih-Ling Tsai, 2005. "Constrained Inverse Regression for Incorporating Prior Information," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 204-211, March.
  2. Eric T. Anderson & Duncan I. Simester, 2004. "Long-Run Effects of Promotion Depth on New Versus Established Customers: Three Field Studies," Marketing Science, INFORMS, vol. 23(1), pages 4-20, February.
  3. Rajiv Lal & David Bell, 2003. "The Impact of Frequent Shopper Programs in Grocery Retailing," Quantitative Marketing and Economics, Springer, vol. 1(2), pages 179-202, June.
  4. Ran Kivetz, 2003. "The Effects of Effort and Intrinsic Motivation on Risky Choice," Marketing Science, INFORMS, vol. 22(4), pages 477-502, December.
  5. Füsun Gönül & Meng Ze Shi, 1998. "Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models," Management Science, INFORMS, vol. 44(9), pages 1249-1262, September.
  6. Wagner A. Kamakura & Michel Wedel, 2003. "List augmentation with model based multiple imputation: a case study using a mixed-outcome factor model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 46-57.
  7. Bolton, R.N. & Lemo, K.N. & Verhoef, P.C., 2002. "The Theoretical Underpinnings of Customer Asset Management," ERIM Report Series Research in Management ERS-2002-80-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  8. Kopalle Praveen K & Neslin Scott A, 2003. "The Economic Viability of Frequency Reward Programs in a Strategic Competitive Environment," Review of Marketing Science, De Gruyter, vol. 1(1), pages 1-41, August.
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Citations

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Cited by:
  1. P. Baecke & D. Van Den Poel, 2012. "Including Spatial Interdependence in Customer Acquisition Models: a Cross-Category Comparison," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/788, Ghent University, Faculty of Economics and Business Administration.
  2. P. Baecke & D. Van Den Poel, 2012. "Improving Customer Acquisition Models by Incorporating Spatial Autocorrelation at Different Levels of Granularity," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/819, Ghent University, Faculty of Economics and Business Administration.
  3. Sander Triest & Maurice Bun & Erik Raaij & Maarten Vernooij, 2009. "The impact of customer-specific marketing expenses on customer retention and customer profitability," Marketing Letters, Springer, vol. 20(2), pages 125-138, June.
  4. Sunil Gupta & Carl F. Mela & Jose M. Vidal-Sanz, 2009. "The value of a "free" customer," Business Economics Working Papers wb092903, Universidad Carlos III, Departamento de Economía de la Empresa.
  5. P. Baecke & D. Van Den Poel, 2010. "Improving purchasing behavior predictions by data augmentation with situational variables," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/658, Ghent University, Faculty of Economics and Business Administration.
  6. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics, Springer, vol. 5(2), pages 163-190, June.
  7. J. D’Haen & D. Van Den Poel, 2013. "Model-supported business-to-business prospect prediction based on an iterative customer acquisition framework," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/863, Ghent University, Faculty of Economics and Business Administration.
  8. Mercedes Esteban Bravo & José M. Vidal-Sanz & Gökhan Yildirim, 2012. "Valuing customer portfolios with endogenous mass-and-direct-marketing interventions using a stochastic dynamic programming decomposition," Business Economics Working Papers wb121304, Universidad Carlos III, Departamento de Economía de la Empresa.

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