Too much choice, too little time—it’s a constant theme of the information age. There are 60,000 apps available for the iPhone, but the benefits of using personally relevant apps can almost be negated by the amount of time it takes to discover them. 16apps is a new web service designed to streamline the process. The service scours users’ Facebook, Twitter, FriendFeed or LastFM accounts for information about their hobbies, interests, lifestyle, character and location. It then uses the data to make personalised app recommendations. For instance, if it detects messages or links on a user’s profile related to politics, it may recommend an app like “Political Tweets”; if it finds swear words, it has been known to recommend “Rude Ringtones”. Although the functionality of the app has had a mixed reception among the social media crowd, the value in the concept is clear. As consumers experience an explosion of choice in more and more areas of life, recommendation engines are becoming indispensable tools. What makes 16apps particularly interesting is that it doesn’t require previous interaction with users in order to discover what they (are) like, since it makes use of openly available data that they’ve already shared, painting a full picture of their ‘digital personality’. It creates an interesting challenge for brands: how to mine the data in a relevant way, without being intrusive or spammy.