Associate Professor of Marketing
Demand Modeling ; User-generated Content ; Online Marketing ; Two-sided Markets ;
The authors measure the value of promotional activities and referrals by content creators to an online platform of user-generated content.To do so, the authors develop a modeling approach that explains individual-level choices of visiting the platform, creating, and purchasing content as a function of consumer characteristics and marketing activities, allowing for the possibility of interdependence of decisions within and across users.Empirically, the authors apply a model to Hewlett-Packard's (HP) print-on-demand service of user-created magazines, named MagCloud. The authors use two distinct data sets to show the applicability of our approach: an aggregate-level data set from Google Analytics, which is a widely available source of data to managers, and an individual-level data set from HP.The results compare content creator activities, which include referrals and word-of-mouth efforts, with firm-based actions, such as price promotions and public relations.The authors show that price promotions have strong effects but are limited to the purchase decisions, whereas content creator referrals and public relations efforts have broader effects that impact all consumer decisions at the platform.The authors provide recommendations as to the level of a firm's investments when 'free' promotional activities by content creators exist. These free marketing campaigns are likely to have a substantial presence in most online services of user-generated content.