Amazon’s already built an implicit web app

Cobweb

In preparation for Defrag, I’ve been trying to organize my thoughts on the implicit web. Previously, I gave an example of how implicit information could improve search. I realized as I was thinking about this last night that there was already a successful implicit application being used by millions of people every day; Amazon’s recommendation system.

It fits well with my idea of the implicit web; it’s using the data passively collected from users behavior to offer up recommendations, there’s no user data-entry required, it’s a behind-the-scenes servant offering up useful information. So if the implicit web’s been in use for years, why do we even need the term?

Amazon is in a very rare position; they have a massive set of trusted data to work with, and they know a lot about their users. This gives them enough information to chew on and produce something useful. Very few other sites have enough breadth (number of users) and depth (information about their user’s behavior) to do anything similar. To do something comparable without owning a site like that, services have to sit on the client side and collect information as the user browses the web.

me.dium is an example of that sort of service. At the moment, they’re offering a very simple service; show me where my friends are surfing, and related sites strangers are visiting that are similar to my current page. The second part is pretty similar to Amazon’s recommendations. The really exciting bit is that once users trust you with the data about where they’re surfing, and what their friends are, you can build some really compelling services. Here’s a few examples of what I’d do with that information:

  • Build an implicit list of favorites based on how often a user visits sites, and how long they spend there. Let them use it as a bookmark toolbar, or even publish it to their friends as their current favorites.
  • Highlight links that other people took most often to leave a page, and show pages they came from most often, giving friends a higher influence.
  • Let the user ‘stumble-upon’ pages that are popular with their friends right now.

I’m really excited about the possiblities, and I’m looking forward to some interesting conversations at Defrag!

Funhouse Photo User Count: 1,251 total, 60 active. Weird, a big jump from yesterday, almost 90 users, but the stats page claims only 22 adds in the last 24 hours. I’m not sure what’s up, but I’m not complaining!

Event Connector User Count: 36 total, 9 active. Not much change in the numbers, but there has been some progress. Tim from New Media Expo has set up a Facebook event for their 2008 show, and has around 100 guests so far. You can try out the connector here, I’m hoping that it will be as popular as it was for Defrag.

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