Daily Deals: Prediction, Social Diffusion, and Reputational Ramifications
Daily deal sites have become the latest Internet sensation, providing discounted offers to customers for restaurants, ticketed events, and services. We undertake a study of the economics of daily deals on the web, first by analyzing 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. 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.
Joint work with Michael Mitzenmacher (Harvard) and Georgios Zervas (Boston University and Yale). www.technologyreview.com/blog/arxiv/27150
Professor John Byers is an Associate Professor of Computer Science at Boston University. He is also Chief Scientist and a member of the Board of Directors at Adverplex, Inc., a quantitative online advertising firm based in Cambridge, MA. D. Byers joined B.U. in 1999 and has had an executive role at Adverplex since the company’s founding in 2005. He received his BA in Computer Science, Economics, and Mathematics at Cornell University (1991), and his Ph.D. in Computer Science at the University of California at Berkeley (1997). Prior to his appointment at B.U., he was a post-doctoral researcher at the International Computer Science Institute in Berkeley. He also served for many years as Affiliated Scientist at Digital Fountain, Inc. (acquired by Qualcomm) and as an Educational Consultant to Hewlett-Packard. Prof. Byers’ research interests are broad and include algorithmic and economic aspects of networking, large-scale data management, and e-commerce. He received the ACM SIGCOMM Test of Time Award in 2009 for his work on scalable loss-resilient multicast; the IEEE ICDE Best Paper Award in 2004 for his work on sensor databases; and a National Science Foundation CAREER Award in 2001. He served terms on the editorial board of IEEE/ACM Transactions on Networking and on the executive committee of ACM SIGCOMM. He is co-chair of the SIGCOMM ’11 Technical Program Committee. www.cs.bu.edu/~byers
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