Reviews, Reputation, and Revenue: The Case of Yelp.com
Executive Summary — In just six years, Yelp.com has managed to crowdsource 20 million reviews of restaurants and other services by creating and leveraging an impressive social network of people who enjoy writing reviews. But can a bunch of amateur opinionators working for free really transform the restaurant industry, where heavily marketed chains and highly regarded professional critics have long had a stronghold? To answer this question, HBS professor Michael Luca combined Yelp reviews with revenues for every restaurant that operated in Seattle, WA at any point between 2003 and 2009. Applying a new method to tease out the causal effect of reviews (separate from the effect of underlying quality), the study shows that a one-star increase on Yelp leads to a 5 to 9 percent increase in revenue. Yet Yelp doesn't work for all restaurants. Chain restaurants —which already spend heavily on branding —are unaffected by changes in their Yelp ratings. This suggests that consumer reviews present a new way of learning in the Internet age, and are fast becoming a substitute for traditional forms of reputation. Key concepts include:
- Online consumer review websites provide more information to consumers than was previously thought to be cost-effective. By relying on user-generated content, Yelp is able to review more products than traditional media such as newspaper reviews. More than 70 percent of Seattle restaurants are on Yelp.
- The impact of consumer reviews depends on the existing reputation of a company or product. Consumer reviews are effective overall, but ineffective when a product has a firmly established reputation (such as a chain restaurant).
- Consumer reviews provide a substitute for more traditional forms of marketing. Other forms of reputation such as chain affiliation may become less influential as websites like Yelp continue to gain traction. Evidence suggests that this pattern is already emerging.
- Consumers rely on simple metrics such as the average rating and the number of reviews, and are more trusting of reviews that are written by "elite" reviewers (as identified by Yelp).
Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp's rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5 percent to 9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant's average rating is affected by the number of reviews and whether the reviewers are certified as "elite" by Yelp, but is unaffected by the size of the reviewers' Yelp friends network.