Scalable Inference of Customer Similarities from Interactions Data Using Dirichlet Processes
Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from which, with homophily as a guiding principle, inferences could be made about the underlying similarities. However, larger networks face a quadratic explosion in the number of potential interactions that need to be modeled. This scalability problem renders probability models of social interactions computationally infeasible for all but the smallest networks. In this paper, we develop a probabilistic framework for modeling customer interactions that is both grounded in the theory of homophily and is flexible enough to account for random variation in who interacts with whom. In particular, we present a novel Bayesian nonparametric approach, using Dirichlet processes, to moderate the scalability problems that marketing researchers encounter when working with networked data. We find that this framework is a powerful way to draw insights into latent similarities of customers, and we discuss how marketers can apply these insights to segmentation and targeting activities.
Volume (Year): 30 (2011)
Issue (Month): 3 (05-06)
|Contact details of provider:|| Postal: 7240 Parkway Drive, Suite 300, Hanover, MD 21076 USA|
Web page: http://www.informs.org/
More information through EDIRC
References listed on IDEAS
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.:
- Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
- George A. Akerlof, 1997. "Social Distance and Social Decisions," Econometrica, Econometric Society, vol. 65(5), pages 1005-1028, September.
- Gatignon, Hubert & Robertson, Thomas S, 1985. " A Propositional Inventory for New Diffusion Research," Journal of Consumer Research, Oxford University Press, vol. 11(4), pages 849-867, March.
- Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
- David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
- Eric T. Bradlow & David C. Schmittlein, 2000. "The Little Engines That Could: Modeling the Performance of World Wide Web Search Engines," Marketing Science, INFORMS, vol. 19(1), pages 43-62, June.
- K. R. Narayanan, 1954. "Freedom in Modern Society," India Quarterly: A Journal of International Affairs, , vol. 10(4), pages 376-381, October.
- Marshall Van Alstyne & Erik Brynjolfsson, 2005. "Global Village or Cyber-Balkans? Modeling and Measuring the Integration of Electronic Communities," Management Science, INFORMS, vol. 51(6), pages 851-868, June.
- Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2008. "Goodness of Fit of Social Network Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 248-258, March.
- Brown, Jacqueline Johnson & Reingen, Peter H, 1987. " Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Oxford University Press, vol. 14(3), pages 350-362, December.
- Sungjoon Nam & Puneet Manchanda & Pradeep K. Chintagunta, 2010. "The Effect of Signal Quality and Contiguous Word of Mouth on Customer Acquisition for a Video-on-Demand Service," Marketing Science, INFORMS, vol. 29(4), pages 690-700, 07-08.
- Bruce G. S. Hardie & Peter S. Fader & Robert Zeithammer, 2003. "Forecasting new product trial in a controlled test market environment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 391-410.
- Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model-based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354.
- Reingen, Peter H, et al, 1984. " Brand Congruence in Interpersonal Relations: A Social Network Analysis," Journal of Consumer Research, Oxford University Press, vol. 11(3), pages 771-783, December.
- Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort?," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 145-159, April.
- Bearden, William O & Etzel, Michael J, 1982. " Reference Group Influence on Product and Brand Purchase Decisions," Journal of Consumer Research, Oxford University Press, vol. 9(2), pages 183-194, September.
- Donald G. Morrison & David C. Schmittlein, 1981. "Predicting Future Random Events Based on Past Performance," Management Science, INFORMS, vol. 27(9), pages 1006-1023, September.
- Park, C Whan & Lessig, V Parker, 1977. " Students and Housewives: Differences in Susceptibility to Reference Group Influence," Journal of Consumer Research, Oxford University Press, vol. 4(2), pages 102-110, Se.
- Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort? Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 165-166, April.
- Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
- Jan Kratzer & Christopher Lettl, 2009. "Distinctive Roles of Lead Users and Opinion Leaders in the Social Networks of Schoolchildren," Journal of Consumer Research, Oxford University Press, vol. 36(4), pages 646-659, December.
- Peter D. Hoff, 2005. "Bilinear Mixed-Effects Models for Dyadic Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 286-295, March.
- Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Oxford University Press, vol. 34(4), pages 441-458, 05.