The Internet has enabled the era of user-generated content, potentially breaking the
hegemony of traditional content generators as the primary sources of “legitimate” information.
Prime examples of user-generated content are blogs and social networking sites, which allow easy
publishing of and access to information. In this study, we examine the usefulness of such content,
consisting of data from blogs and social networking sites in predicting sales in the music industry.
We track the changes in online chatter for a sample of 108 albums for four weeks before and after
their release dates. We use linear and nonlinear regression to identify the relative significance of
online variables on their observation date in predicting future album unit sales two weeks ahead
Our findings are as follows: (a) the volume of blog posts about an album is positively correlated
with future sales, (b) greater increases in an artist’s Myspace friends week over week have a
weaker correlation to higher future sales, (c) traditional factors are still relevant – albums released
by major labels and albums with a number of reviews from mainstream sources like Rolling Stone
also tended to have higher future sales. More generally, the study provides some preliminary
answers for marketing managers interested in assessing the relative importance of the burgeoning
number of “Web 2.0” information metrics that are becoming available on the Internet, and how
looking at interactions among them could provide predictive value beyond viewing them in
isolation. The study also provides a framework for thinking about when user-generated content
influences decision making
