Articles

© Marketing Science, 2012
Volume: 31 | Issue: 3 | Pages: 521-543

Publication type: Journal article

Research Archive Topic: Marketing

Abstract

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. These data include consumers' thoughts, beliefs, experiences, and even interactions. In this paper, we propose an approach to transform the Web 2.0 to a large, yet readily available, marketing field test. Exploring such online user-generated content offers the firm an opportunity to "listen" to consumers in the market in general and to its own customers in particular. By observing what customers write about the products in the category, the firm can get a better understanding of the market structure, the competitive landscape, and the features discussed about its and the competition's products. The difficulty in obtaining such insights is that consumers' postings are often not easy to syndicate. A decoding mechanism is needed in order to transform these raw qualitative data into meaningful knowledge. To address these issues, we developed an advanced text mining approach (called CARE) and combine it with semantic network analysis tools. We demonstrate this approach using two cases; sedan cars and diabetes drugs; generating sensible perceptual maps and meaningful insights, without interviewing a single consumer.

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