Yet this wealth of consumer-generated content can be both a blessing and a curse. A new approach, described in a study by Oded Netzer, the Philip H. Geier Jr. Associate Professor at Columbia Business School, offers a way to efficiently aggregate and analyze this content. The study, co-authored with Ronen Feldman and Moshe Fresko of Hebrew University, and Jacob Goldenberg, visiting professor at Columbia Business School and Professor of Marketing at Hebrew University, shows how text mining -- the process of extracting useful information from unstructured text -- combined with network-analysis tools can help businesses leverage the web as a marketing research playground, generating meaningful insights on market structure and the competitive landscape without asking consumers a single question.

The researchers developed a text-mining tool specifically designed for the complexity of consumer forums, as well as a method of converting this information into quantifiable perceptual associations and similarities between brands. Companies can use this method to monitor their market positions over time -- with greater detail and at a lower cost than through traditional methods based on sales and survey data.

The method proved successful in empirical tests, including one focused on consumer forums about sedan cars. In the first test, the researchers downloaded data from the sedan forum Edmunds.com, and text mined more than 860,000 consumer messages, consisting of close to six million sentences posted by about 76,000 unique consumers between 2001 and 2007. Using their combination of text mining and network-analysis techniques, they created visual maps of consumer perceptions and discussions about 169 different sedan cars. The maps can be used to evaluate the competitive market structure, and assess the effectiveness of marketing campaigns. The study demonstrates how a large scale marketing campaign by Cadillac aimed at positioning Cadillac as a stronger rival for import luxury cars was indeed able to move the needle in terms of consumers' top-of-mind association of Cadillac.

This new method can also be used to analyze more structured textual data such as blogs, reviews, and articles to explore consumer perceptions and opinions.

Note: If no author is given, the source is cited instead.

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