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Marketing insights from text analysis |
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| Authors: | Berger Jonah Packard Grant Boghrati Reihane Hsu Ming Humphreys Ashlee Luangrath Andrea Moore Sarah Nave Gideon Olivola Christopher Rocklage Matthew |
| Institution: | 1.Wharton School at the University of Pennsylvania, Philadelphia, PA, USA ;2.Schulich School of Business, York University, Toronto, Canada ;3.Wharton Risk Center and Marketing Department, University of Pennsylvania, Philadelphia, PA, USA ;4.University of California, Berkeley, USA ;5.Medill School of Journalism, Media, and Integrated Marketing Communications, Northwestern University, Evanston, IL, USA ;6.Tippie College of Business, University of Iowa, Iowa City, IA, USA ;7.Alberta School of Business, University of Alberta, Edmonton, AB, Canada ;8.Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA ;9.University of Massachusetts, Boston, MA, USA ; |
| Abstract: | Language is an integral part of marketing. Consumers share word of mouth, salespeople pitch services, and advertisements try to persuade. Further, small differences in wording can have a big impact. But while it is clear that language is both frequent and important, how can we extract insight from this new form of data? This paper provides an introduction to the main approaches to automated textual analysis and how researchers can use them to extract marketing insight. We provide a brief summary of dictionaries, topic modeling, and embeddings, some examples of how each approach can be used, and some advantages and limitations inherent to each method. Further, we outline how these approaches can be used both in empirical analysis of field data as well as experiments. Finally, an appendix provides links to relevant tools and readings to help interested readers learn more. By introducing more researchers to these valuable and accessible tools, we hope to encourage their adoption in a wide variety of areas of research. |
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