With Defrag fast approaching, I’ve been spending some cycles thinking about what the Implicit Web actually is, and where it’s going. When I’m staring at this sort of problem, a technique I find really useful is "stamp collecting". Gather as many examples as possible, list their important properties, group them into clusters and look at what patterns emerge.
Here’s my current list of Implicit Web services currently out there, with a couple that are on the borderline of the term. I’ve not got enough to meaningfully group them, so they’re alphabetical:
Adaptive Blue – More of a semantic web application, but they do offer a Firefox extension. Being client-based is a distinguishing feature of implicit web apps, since that’s the only way I know to get access to the user data needed.
Amazon – Their recommendation system is the grand-daddy of a lot of the apps that take raw information on user’s behavior, run some magic algorithms, and return something useful back to the customer. It’s a hard trick for most startups to repeat, since almost nobody has access to the Amazon’s breadth of data. This is why client-based solutions that can track behavior across many sites seem like the only practical solution.
last.fm – A true implicit web app, they have client-based tracking of the user’s behavior, they piggy-back on other people’s applications to gather their data and use that to return Amazon-style recommendations. It does make me wonder about the ‘web’ part of the term though, since that seems to imply web browsing. Maybe ‘implicit internet’ would be more appropriate?
me.dium – Another app that fully fits the term. A unique feature is that they use the social graph to combine information from multiple users, which I think is a very promising area for implicit web applications. Being able to pool data from your friends is a great way of discovering relevant new content.
MySportsNet.ca – This is one I came across relatively recently. It’s a client-side app that monitors your browsing, and tailors a sports portal site to match your interests based on that data. What’s really interesting is that it’s aimed at a mainstream audience of sports fans, rather than geeky early adopters. I know from my game career that the sports audience is massive, and willing to pay for something ties into their passion, so I’ll be following its progress closely. The only audience I know that’s similar is music, and it’s relevant that the most successful implicit app so far, last.fm, tapped into that demand.
tape failure – This is a service I’ve only read about, but unfortunately their site seems to be down at the moment. They’re not an implicit web app at all, but it does seem like they have a good solution to the browsing data collection problem.
Let me know if you think I’m missing any. I may put together a page tracking new services, since I think we’re going to be getting a lot more over the next year.
Funhouse Photo User Count: 1,916 total, 92 active. The proportion of profile-box adds was a bit higher this time, which is promising because it scales a bit more virally than the product directory.
Event Connector User Count: 84 total, 9 active. Not much happening on this front.