Whenever I tell people about Foursquare, they inevitably say something like, “Oh, you mean the check-in app?” It’s true that Foursquare got its start by popularizing the term “check-in” and by adding game elements like badges to their app. But today, Foursquare does much more. Namely, their bread and butter has become personalized recommendations. With thirty million users and literally billions of check-ins, users are demonstrating which places they like, which places their friends like, and how often they go back to those places. As a result, instead of something like Yelp, which only shows places based on how someone feels about a restaurant or venue, Foursquare factors in whether or not someone went there, if they returned, and if they explicitly liked or disliked it.
If you’ve ever read one of Yelp’s essay-length reviews, you don’t have to look far to find a one-star review with someone saying, “Normally, I love hole-in-the-wall Thai places, but this one was the worst! I didn’t like the way the chairs felt , which made my day even more horrible since I just broke up with my boyfriend earlier in the day...” Foursquare, on the other hand, shies away from lengthy reviews and limits the user to tweet-length tips and simple "liking" or "disliking" of the venue. That way you can recommend one or two things and that’s it. This results in Foursquare showing unique results to each person based on where you’ve been before, where your friends have been, where you're located at that moment, the time of day, and a host of other variables.
Foursquare CEO Dennis Crowley has explained the intelligence of the app before, using one very cool example: the idea of authenticity. He explains that an American user who spends several months abroad in Spain could, for example, check in at tapas bars there. Then when s/he returns to the States and checks into a NYC tapas bar, the check-in is given a greater authenticity value since the person would probably know what is more authentic Spanish food than someone who has never been to Spain. In other words, the NYC tapas bar would have a higher rating because of her check-in than other tapas bars. This is just one form of intelligence built into the Foursquare app, though Crowley says Foursquare data scientists are constantly adding more with every iteration.
Even their business model leads to more relevant search results. Essentially, they sell merchant tools so that if I check-in at several coffee places, it might then tell me in the app that Starbucks is having a special for coffee lovers only. Starbucks could set parameters such as “only target people who have checked into 5 coffee places in the last week.” While many forms of marketing/advertising could interrupt the usual flow of what the user wants, in this case, even the advertising tries to be relevant to something I’m interested in. Check out Foursquare at the links below: