The power of aggregated attention data

Feed readership represents a significant disconnect between traffic data and actual content consumption. Aggregated attention data is going to play a big role in bridging that gap.

Brent Simmons recently noted this gem from Nick Bradbury:

“…future releases of FeedDemon, NetNewsWire and NewsGator Inbox are all planning to support APML.”

This is a logical next step for these products, and they’re not alone – Bloglines is also planning APML support. From a users’ perspective, it will address one of the features I’ve been sorely missing from NetNewsWire – that my feeds will be sorted by most read/bookmarked/etc across all my synched locations. But there are larger implications here.

What shared attention data represents is a powerful shift in how we collect information and what we do with the content we consume. It goes beyond publishing reading lists, bookmarks and favorites. It is a much more passive way of applying importance to the information that we encounter. By the simple act of consuming information sources (i.e. reading, clicking, etc.), we are ranking those sources, without having to do anything outside our normal workflow.

Publishing those rankings in a standard attention data format means that you can easily share with your friends and readers the sites that you read most often, not just a list of all your feeds in alphabetical order.

But the real power of standardized, published attention data lies in it’s aggregation. That attention data can provide much richer traffic and consumption statistics than simple feed counts alone. It provides a mechanism for content providers to better see who is actually reading their content, as opposed to just subscription numbers.

Aggregated attention data is going to significantly affect how we assess traffic, flow, and popularity. In other words, publishers will have a better picture of their audience. And that will affect advertising, income, and the shape of the web.

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About this article

Green Galoshes is a weblog written by Justin D. Henry. This entry was published on or around October 19, 2007.

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