Daily Deals: Prediction, Social Diffusion, and Reputational Ramifications

December 8, 2011
Mudd 1127
Speaker: Giorgos Zervas


Daily deal sites have become the latest Internet sensation, providing discounted offers to customers for restaurants, ticketed events, services, and other items. We begin by undertaking a study of the economics of daily deals on the web, based on a dataset we compiled by monitoring Groupon and LivingSocial sales in 20 large cities over several months. We use this dataset to characterize deal purchases; glean insights about operational strategies of these firms; and evaluate customers' sensitivity to factors such as price, deal scheduling, and limited inventory. We then marry our daily deals dataset with additional datasets we compiled from Facebook and Yelp users to study the interplay between social networks and daily deal sites. First, by studying user activity on Facebook while a deal is running, we provide evidence that daily deal sites benefit from significant word-of-mouth effects during sales events, consistent with results predicted by cascade models. Second, we consider the effects of daily deals on the longer-term reputation of merchants, based on their Yelp reviews before and after they run a daily deal. Our analysis shows that while the number of reviews increases significantly due to daily deals, average rating scores from reviewers who mention daily deals are 10% lower than scores of their peers on average.

Brief Bio

Giorgos Zervas is a Simons Postdoctoral Fellow at Yale and an Affiliate at the Center for Research on Computation and Society (CRCS) at Harvard. He is interested in the descriptive analysis of internet markets and the ways in which economic information is shaping them. He recently completed his PhD at Boston University under the supervision of John Byers and Michael Mitzenmacher (from Harvard).

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