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Choice Models and Customer Relationship Management

Author

Listed:
  • 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

Suggested Citation

  • Wagner Kamakura & Carl Mela & Asim Ansari & Anand Bodapati & Pete Fader & Raghuram Iyengar & Prasad Naik & Scott Neslin & Baohong Sun & Peter Verhoef & Michel Wedel & Ron Wilcox, 2005. "Choice Models and Customer Relationship Management," Marketing Letters, Springer, vol. 16(3), pages 279-291, December.
  • Handle: RePEc:kap:mktlet:v:16:y:2005:i:3:p:279-291
    DOI: 10.1007/s11002-005-5892-2
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    References listed on IDEAS

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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, 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.
    3. Gupta, Sunil & Mela, Carl F. & Vidal-Sanz, Jose M., 2009. "The value of a "free" customer," DEE - Working Papers. Business Economics. WB wb092903, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    4. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.
    5. Song Yao & Carl F. Mela, 2008. "Online Auction Demand," Marketing Science, INFORMS, vol. 27(5), pages 861-885, 09-10.
    6. 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.
    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. Andrés Musalem & Yogesh V. Joshi, 2009. "—How Much Should You Invest in Each Customer Relationship? A Competitive Strategic Approach," Marketing Science, INFORMS, vol. 28(3), pages 555-565, 05-06.
    9. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    10. 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.
    11. Mizuno, Makoto & Saji, Akira & Sumita, Ushio & Suzuki, Hideo, 2008. "Optimal threshold analysis of segmentation methods for identifying target customers," European Journal of Operational Research, Elsevier, vol. 186(1), pages 358-379, April.
    12. repec:eee:joreco:v:36:y:2017:i:c:p:218-224 is not listed on IDEAS

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