The Internet is a big place, and expanding every hour. Because it is so vast, and the resources out there are so many, it's in everyone's best interest -- other than SEO gamers -- to arrive at the best possible search results.
Companies already know this, of course. They work hard at coding their sites with the right keywords - those that depict what they do best - so you can find them.
We've already discussed Yahoo!Search initiative for an open search ecosystem, one based on semantic web standards. This kind of search will comb the next generation of internally tagged web documents for their meaning, not just word patterns. Mahalo is an example of a next-generation search engine whose results are the output of human decisions.
But we already have a vast and largely untapped pool of human search results: the sum of social media.
Think about it: every time you engage in social media, you are essentially tagging and collating information:
- photo captions on Flickr;
- topical bookmarks on de.licio.us, Ma.gnolia, and Digg;
- human relationships on Facebook, Twitter, and MySpace;
- and a host of others.
Social media permeates modern cyberculture.
Perhaps best of all, this social search activity is directly attributed to its users, each of whom have digital footprints identifying their interests, associations, and level of activity. Think of this as PageRank 2.0: a deeply granular measure of authority created by and for people who search.
Here's where things get interesting, particularly for marketers.
A social search engine wouldn't simply tap into the expanding reservoir of human-sorted data sorted by our various layers of social media, it would vividly quantify its creators. You could easily determine the aggregated interests of 25-34 working, married females who are interested in automobiles (I'm just saying), for instance -- or any other social profile. Zeitgeist on steroids, complete with geotagging and all the other data points which fall under the social media blanket.
A social search engine would also presumably recognize its users. Search for "automobiles," and the results would be outputted based on the social media footprint of its user. The bigger your social media footprint, the more relevant your search results. And the more you contribute to the system. Users get out in proportion to what they put in.
This approach blows the artificial intelligence approach of the current generation of search engines out of the water, while outscaling top-down human efforts of projects like Mahalo.
I've mused before about the future growth of personal media and artificial intelligence (AI) agents as discovery channels. Would the social search engine get us closer to the substance part in relationships? Would it allow us to find more interesting departures on what we're attuned to?
Would this kind of tagging allow advertisers to provide more pertinent content so that much of the Internet can remain free? The Internet runs on ad billions, after all.
[map of the World Wide Web, courtesy of Opte.org]