Why data science matters to Foursquare

Interesting… Since its most recent update, Foursquare users now spend 30% more time with the check-in app. And it wouldn’t have been possible without the input of data scientist Blake Shaw

this via the Guardian…

When a user checks in to Foursquare, the location-sharing app does more than just check them in. It also notes the location using the phone’s GPS tracker, the strength of any surrounding Wi-Fi networks and also collects data on the distance to the closest mobile towers. And when this data is collected from a community of 40 million (and more than five billion check-ins), it gives the company an incredibly valuable data set.

Breaking it down further, this means that when a user attempts to check in, Foursquare can predict where they are, even if they’re in the underground basement of a coffee shop without any reception. How? Because after four years of checking in various users, another Foursquare user has probably faced a similar lack of signal in the same venue and connected to a wifi network to check in.

For those of you unfamiliar with the app, Foursquare is a social network that allows users to check in to specific locations, such as coffee shops, restaurants, bars and offices. Once users check in, they traditionally receive a pop-up notification containing a useful tip from someone. Those who check in at the Guardian’s office, for example, might receive a notification suggesting they visit the gallery at the foot of the building.

It’s these types of tips that make the app worthwhile. If you’re looking for a good coffee shop or hidden gem in a new city, for example, chances are that Foursquare users have recommended a nearby place for you to visit.

Source: Guardian




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