In terms of recent web start-ups, one of the hottest areas of growth has been the emergence of “people search” engines. While Google is the search behemoth, there are certainly enough gaps left for startups to fill—specifically in the area of a>
With data showing that close to 30% of all searches on Google and Yahoo are for specific people, or at least people-related, “people search” is a significant chunk of the search pie that these start-ups are all looking to go after. While Google has a breadth of information and indexes a tremendous amount of data, figuring out which “John Smith” you are looking for can be an almost impossible task. So for the 99.9% of individuals who aren’t celebrities, sites like PeekYou.com (which I have developed and run), Wink, Spock and ZoomInfo have sprung up—search engines focused strictly on finding individuals with a presence on the web.
With such crowded activity in terms of companies jockeying for the top position in this space, how will one surpass as a leader? I see parallels between the a> wars of today and the search engine wars of the late 90’s. While we, along with the other players, are scouring the web to pool information and profiles, ultimately it will be people matching and the identification of specific individuals and their correlating online identities that will determine success. In such, the people search battle comes down to best understanding the semantic web and its applications to people search.
Why did Google become the preferred search engine and AltaVista fade? AltaVista often had millions more pages of search results, but there was no relevancy among the first few pages of results. The development of Google’s PageRank system gave Google a means of triangulation, giving meaning to any single webpage within the context of search. PageRank was an attempt to apply semantics, or meaning, to trillions of otherwise meaningless words scattered across a vast internet where anything can be published. By serving more relevant results, Google easily surpassed its rivals. It is always about quality and accuracy of results more than pure numbers.
When it comes to people search, there needs to be accuracy in terms of matching up links to specific individuals – and this require a strong understanding of the semantic web. Otherwise your search engine will just spit out non-sensical data. In that case, why not just continue to use Google to find people?
The essence of people search is the ability to construct search results using “static notions” such as name, location and employer / university as mileposts to triangulate data from across the web. These mileposts will be the basis by which search engines will achieve a unique single profile of each individual online rather than a multitude of profiles or search results all correlating to a single identity.
Much like how Google achieved market penetration, semantic web notions are the key to success in the emerging people search space.
