66 Pages Posted: 23 Apr 2011 Last revised: 6 Nov 2016
Date Written: December 20, 2011
Web 2.0 provides gathering places for internet users in blogs, forums, and chat rooms. These gathering places leave footprints in the form of colossal amounts of data regarding consumers’ thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach for firms to explore online user-generated content and “listen” to what customers write about their and the competitors’ products. Our objective is to convert the user-generated content to market structures and competitive landscape insights. The difficulty in obtaining such market-structure insights from online user-generated content is that consumers’ postings are often not easy to syndicate. To address these issues, we employ a text-mining approach and combine it with semantic network analysis tools. We demonstrate this approach using two cases - sedan cars and diabetes drugs, generating market-structure perceptual maps and meaningful insights without interviewing a single consumer. We demonstrate the validity of the approach by comparing a market structure based on user-generated content data with market structure derived from more traditional sales and survey-based data.
Suggested Citation: Suggested Citation
Netzer, Oded and Feldman, Ronen and Goldenberg, Jacob and Fresko, Moshe, Mine Your Own Business: Market-Structure Surveillance Through Text Mining (December 20, 2011). Columbia Business School Research Paper No. 12-2. Available at SSRN: https://ssrn.com/abstract=1816494 or http://dx.doi.org/10.2139/ssrn.1816494
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