Big data dining
If big data dining sounds like your cup of tea, then Uber’s new restaurant guide might be right up your alley.
Instead of relying on user-submitted reviews like on Yelp or one critic’s assessment from The New York Times, Uber is hoping to use its rider data to determine each city’s most popular restaurants, reports TechCrunch. To create its Best Of lists, Uber looked at restaurants where users have requested rides to the most. For example, its top 10 brunch spots are determined by spots that receive the most traffic on weekends, while best fine dining are places where most UberBlack or UberSelect riders frequent. The most interesting is local favorites, which identifies businesses where the same rider repeatedly visits.
The restaurant picks skew on the expensive side, which makes sense given the data comes from people who are well-to-do enough to regularly take Uber to lunch and dinner.
Although it’s not clear how often the list updates, Uber says it will adjust the rankings frequently based on how trip data changes. This also helps the company take into account new businesses that may have gained popularity in recent months.
At launch, Uber’s restaurant guides are available in 12 US cities. Not surprisingly, they center around major metropolitan areas with larger Uber riderships, like New York, Chicago, Boston, Los Angeles, and Dallas. But take these recommendations with a grain of salt… after all, it seems to suggest that Dominique Ansel Bakery of the 2013 cronut craze is still “up and coming.”
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