- Apr 12, 2001
Foursquare's new automatic recommendation service, initially introduced on Android in August, is rolling out to iPhone users. The company has released a new version of its iOS app today, which introduces a redesign and will give a "few thousand" users access to the feature.
With the new recommendation system, Foursquare runs continually in the background, monitoring location to provide recommendations on nearby restaurants and other venues. It will also offer information on popular food and beverage choices following a check in, pulling data from comments that users have left about each venue.
While only a few thousand iPhone users will get access to the feature today, the company plans to continue rolling out the service to additional users as it did on the Android platform.Today we're excited to start rolling out this smarter Foursquare. Here's how it will work: when you sit down to dinner, we might ping you with the can't-miss dish on the menu (like the screenshot from a sushi bar below). Or when you arrive in a new neighborhood or city, we'll suggest a few places that your friends love (like below, after you've wandered into a new neighborhood). It's like having a ton of local friends stuffed in your pocket wherever you go.
Because it's powered by billions of check-ins, it's also smart: we're going to ping you when you sit down at a new place where your friend left a tip, not when you're on your daily walk to work. And using this feature doesn't check you in; this isn't for sharing, just for making sure you don't miss great things.
Along with the rollout of the recommendation system, Foursquare's newest update introduces a simplified design that shows only the most recent check-in for each friend. Additional check-ins are now accessed via profile pages, and a newly introduced "nearby" button displays friends that are located in the vicinity.
Foursquare is an iPhone-only app that can be downloaded from the App Store for free. [Direct Link]
Article Link: Foursquare for iOS Updated With Redesign, Real-Time Recommendations