Vol. 31, No. 3, May–June 2012, pp. 521–543 ISSN 0732-2399 (print) ISSN 1526-548X (online) http://dx.doi.org/10.1287/mksc.1120.0713 © 2012 INFORMS Mine Your Own Business: Market-Structure Surveillance Through Text Mining Oded Netzer Graduate School of Business, Columbia University, New York, New York 10027,
[email protected] Ronen Feldman School of Business Administration, Hebrew University of Jerusalem, Mount Scopus, Jerusalem, Israel 91905,
[email protected] Jacob Goldenberg School of Business Administration, Hebrew University of Jerusalem, Mount Scopus, Jerusalem, Israel 91905; and Columbia Business School, New York, New York 10027,
[email protected] Moshe Fresko Jerusalem, Israel 91905,
[email protected] eb 2.0 provides gathering places for Internet users in blogs, forums, and chat rooms. These gathering places Wleave footprints in the form of colossal amounts of data regarding consumers’ thoughts, beliefs, experi- ences, 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 their 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 compare a market structure based on user-generated content data with a market structure derived from more traditional sales and survey-based data to establish validity and highlight meaningful differences.