Computational Consumer Segmentation and Brand Management

We leverage large-scale social media data, text data, and machine learning methods, to accomplish three brand management goals: identify consumer personality segments (Study 1), identify the themes associated with brands liked by those segments (Study 2), and show that consumers tend to like brands that “fit” their personalities (Study 3).



Citation:

Ada Aka, Christopher Olivola, Sudeep Bhatia, and Gideon Nave (2020) ,"Computational Consumer Segmentation and Brand Management", in NA - Advances in Consumer Research Volume 48, eds. Jennifer Argo, Tina M. Lowrey, and Hope Jensen Schau, Duluth, MN : Association for Consumer Research, Pages: 825-830.

Authors

Ada Aka, University of Pennsylvania, USA
Christopher Olivola, Carnegie Mellon University, USA
Sudeep Bhatia, University of Pennsylvania, USA
Gideon Nave, University of Pennsylvania, USA



Volume

NA - Advances in Consumer Research Volume 48 | 2020



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