Predicting Consumer Brand Recall and Choice Using Large-Scale Text Corpora
We present a novel approach to predict core aspects of consumer memory by leveraging advances in machine learning (ML) and natural language processing (NLP). Specifically, we predict the likelihood that consumers will recall specific brands within a product category using word embeddings models trained on large scale text corpora.
Citation:
Zhihao Zhang, Aniruddha Nrusimha, and Ming Hsu (2018) ,"Predicting Consumer Brand Recall and Choice Using Large-Scale Text Corpora", in NA - Advances in Consumer Research Volume 46, eds. Andrew Gershoff, Robert Kozinets, and Tiffany White, Duluth, MN : Association for Consumer Research, Pages: 204-207.
Authors
Zhihao Zhang, University of California Berkeley, USA
Aniruddha Nrusimha, University of California Berkeley, USA
Ming Hsu, University of California Berkeley, USA
Volume
NA - Advances in Consumer Research Volume 46 | 2018
Share Proceeding
Featured papers
See MoreFeatured
Unexpected-Framing Effect: Impact of Framing a Product Benefit as Unexpected on Product Desire
Monica Wadhwa, INSEAD, Singapore
Christine Kim, Hong Kong University of Science and Technology
Amitava Chattopadhyay, INSEAD, Singapore
Wenbo Wang, Hong Kong University of Science and Technology
Featured
Approach and Loss Aversion: Consumer Responses to Approaching and Receding Stimuli in Advertising
Lana Mulier, Ghent University, Belgium
Iris Vermeir, Ghent University, Belgium
Hendrik Slabbinck, Ghent University, Belgium
Featured
Teaching Consumer Resistance in Jamaica: Subvertising in Action
Michelle Renee Nelson, University of Illinois at Urbana-Champaign, USA
Yanyun (Mia) Wang, University of Illinois at Urbana-Champaign, USA
Kathy Tian, University of Illinois at Urbana-Champaign, USA
Gail Ferguson, University of Illinois at Urbana-Champaign, USA
Rachel Powell, CDC Foundation
Candace Wray, University of West Indies