Learning From Highly Unstructured Data: Insight From Videos, Images and Audio

Consumer researchers and marketing managers alike are increasingly confronted with highly unstructured data. Text, images, audio, and video provide valuable sources of information, but this content is often non-numeric, multi-faceted, and difficult to parse. How can we better use these exciting resources to test theory and uncover insight?


Reto Hofstetter, Jonah Berger, Aradhna Krishna, Marc Bravin, Melanie Clegg, Marc Pouly, Prashant Rajaram, Puneet Manchanda, Jochen Hartmann, Verena Schoenmueller, Yonat Zwebner, Jacob Goldenberg, Oded Netzer, Na Kyong Hyun, and Michael Lowe (2021) ,"Learning From Highly Unstructured Data: Insight From Videos, Images and Audio", in NA - Advances in Consumer Research Volume 49, eds. Tonya Williams Bradford, Anat Keinan, and Matthew Matthew Thomson, Duluth, MN : Association for Consumer Research, Pages: 808-813.


Reto Hofstetter, University of Lucerne
Jonah Berger, penn
Aradhna Krishna, Univ. of Michigan, Ann Arbor
Marc Bravin, University of Applied Sciences and Arts Lucerne
Melanie Clegg, University of Lucerne
Marc Pouly, University of Applied Sciences and Arts Lucerne
Prashant Rajaram, Ivey Business School at Western University
Puneet Manchanda, University of Michi
Jochen Hartmann, University of Hamburg
Verena Schoenmueller, Bocconi University
Yonat Zwebner, IDC Herzliya
Jacob Goldenberg, Interdisciplinary Center
Oded Netzer, Columbia Business School
Na Kyong Hyun, Georgia Tech
Michael Lowe, Georgia Tech


NA - Advances in Consumer Research Volume 49 | 2021

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