There’s no doubt that the biggest development in the web ecosystem throughout the past 5 years has been social media, and specifically, peer to peer communication channels.
But while the focus has been on these CHANNELS, I’d argue that what is more important in the modern digital landscape is CONTENT. While to the novice user Twitter and Facebook appear to be text-only distribution engines (tweets and status updates are textual stanzas after all), their power lies in transmedia aggregation. As both platforms modify their platforms to allow for in-line content display, it becomes more apparent that copy is becoming less important. Video, graphics, web-apps, long-form articles, games, audio and the like are the content wrappers of today.
Further, as Facebook and Twitter feeds become more saturated with content, these channels are losing their hold as the most useful content distribution and consumption platforms. For every 15 links I click on, only 3 or so are of any interest to me. There is, however, a solution to this epidemic. Enter the age of the discovery engine.
There are three types of discovery engines:
- Thematic Aggregators
- Social Bookmarking Aggregators
- Algorithmic Taste Profile Engines
The thematic aggregators are largely emanating from the Tumblr blogging platform. Instead of distributing content from a single authored source (like New York Times, Pitchfork or ABC.com), there are digital properties that aggregate from a multitude of sources with similar subject matter (and typically cut the useless junk).

Devour.com: one of my favorite video suggestion engines.
Social bookmarking channels like StumbleUpon, Reddit, Delicious and Digg have been around for years but have recently begun to pick up steam within the mainstream social sphere. While not typically thematically driven, these platforms aggregate peer-reviewed and rated content and are segmented by semantic tags and descriptions.

StumbleUpon’s Interest Engine
Perhaps my favorite of the three, algorithmic taste profile engines got their mainstream start thanks to the smart engineers (like my friend Andreas Weigend) at Amazon.com. The modern discovery engine was born after the scientists realized that I, the user, might be interested in knowing what those in my social circle liked or bought. Equally useful outside of the e-commerce vertical, these algorithmic engines are driving content discovery and consumption now more than ever. YouTube suggests videos I’d like; Pandora offers up personalized music playlists that would appeal to me; even Netflix has developed their platform with a discovery engine value-add. Instead of being a simple video distribution service, they have constructed a mathematical algorithm that suggests movies and TV shows based on A) what the user has consumed in the past, and B) what the user has liked or disliked in the past. (See their Netflix Prize initiative for an even more in depth look at their discovery engine and efforts to continue enhancing it.)

The gold-standard of recommendation engines, Netflix.
Discovery engines hold both consumer and business value — and are driving the future of content distribution, consumption and monetization. I predict we’ll be seeing social media channels partner up with or construct proprietary discovery engines to allow for a better, more personalized user experience. But why stop there?