I’ve been attending the Future of Web Applications conference in London. I spoke to several attendees in the evening and the general perception was that the event had been weaker than usual so far. Complaints concerned uninspiring sessions, lack of deep technical content, and information on HTML 5 that was really nothing new.
That said, several said how much they enjoyed a session from Hilary Mason at bit.ly on data analysis. Bit.ly does url shortening, with 70% of so of its traffic coming from Twitter clients, and Mason is a statistical expert who has worked on analysing and visualising the resulting data. She told us, for example, that news links are more popular than sports links, and sports links more popular than food links. She was also able to discover the best time to post a link for any particular Twitter account, if you want maximum clicks. There is no quick way to discover this, so this type of analysis is valuable for companies using Twitter as a PR tool. Another snippet of information was the half-life of a typical bit.ly link – in other words, the time interval by which it has recorded 50% of its likely total clicks – which in the example she showed us was between 20 and 25 minutes.
The consequence was that I went into the next session, on social gaming, with data analysis on my mind. The session was presented by Kristian Segerstrale at Playfish, part of Electronic Arts focused on casual games for Facebook and the like. Gaming by the way is a huge part of Facebook, accounting for 30% to 40% of overall engagement, according to Segerstrale. As an insight into the future of gaming, it was a good session, but perhaps did not connect well with typical FOWA attendees.
Nevertheless, Segerstrale made a compelling point about how his company’s games evolve, which is also applicable to other kinds of web applications. He said that there is intense analysis of what works and what does not work, based on the flow of data that is available with web applications. You can see who is playing, when they are playing, which features are used, and get a level of insight into the strengths and weaknesses of your application which is typically unavailable for desktop applications. I imagine this works particularly well within Facebook, because of the rich user profile information there. If you take advantage of that data, you can get a lead over the competition; if you fail to make use of it, you will likely fall behind. There is now a data analytics skills gap, Segerstrale told us.
It was thought-provoking to see how data analytics was a common thread between such different sessions.