A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights

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dc.contributor.advisorDu, Rex Y.
dc.contributor.advisorBlair, Edward A.
dc.contributor.committeeMemberHu, Ye
dc.contributor.committeeMemberFrancia, Arthur J.
dc.contributor.committeeMemberKamakura, Wagner A.
dc.creatorLiutec, Carmen M.
dc.date.accessioned2018-03-02T21:36:33Z
dc.date.available2018-03-02T21:36:33Z
dc.date.createdAugust 2013
dc.date.issued2013-08
dc.date.submittedAugust 2013
dc.date.updated2018-03-02T21:36:34Z
dc.description.abstractWe develop a novel approach for modeling new product trial and early repeat purchase behavior, and we apply this approach in the context of consumer packaged goods. Our approach takes advantage of the cross-individual, cross-product, cross-time data that is increasingly available from retail customer relationship management programs as well as research panels. It enables us to account for differences in consumers’ intrinsic preferences for new products as well as for differences in their responsiveness to marketing variables, during both trial and early repeat purchases. By leveraging these uncovered individual differences, we attempt to achieve three goals. First, we aim to improve the accuracy of post-launch sales forecasts based on data from a period that can be as short as two to three months, tapping into the fact that each individual trial or early repeat purchase observed during the post-launch period sends a different signal about the new product’s sales potential. Second, we aim to provide more informative diagnostics for managers to act upon. (e.g., how to re-position the new product or target it for a particular consumer segment). Finally, we aim to investigate potential empirical regularities regarding consumer responses to new products (e.g., potential differences in responsiveness to marketing variables between early and late triers).
dc.description.departmentMarketing and Entrepreneurship, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/2783
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectNew product models
dc.subjectBayesian models
dc.titleA Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeC. T. Bauer College of Business
thesis.degree.departmentMarketing and Entrepreneurship, Department of
thesis.degree.disciplineMarketing
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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