Facebook’s Answer to Big Data: Creating An Internal Search Engine to Rival Google

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Big data is something Facebook knows a little bit about. The user base of Facebook has grown to astronomical proportions, with now more than 1 billion users, and 743 million of them are active.

Data is bombarding Facebook at a velocity, variety and volume that is so vast, its one of the main reasons for the creation of the Graph Search – and to eventually kill the clout of search behemoth, Google.

Preview: Graph Search: A Great New Tool or Yet Another Threat to Privacy?

Image of Facebook’s Prineville data center courtesy of Jolie O’Dell, Flickr

Image of Facebook’s Prineville data center courtesy of Jolie O’Dell, Flickr

The idea behind Graph Search is simple, it allows you to leverage Facebook’s data on its users to get results that also contain a social layer of information. Essentially, you’re able to search your Facebook profile and discover more intimately what your connections are interested in.

On Facebook’s Graph Search privacy page, it explains that Graph Search helps you find people, places and things – allowing you to explore Facebook in a whole new way. Some examples of searches you might look up are: My Friends who live in San Francisco, My Friends who like surfing, Photos of my friends, and Places my friends like. This allows you to look up anything shared with you on Facebook, and others can find stuff you’ve share with them, including content set to Public. Which means different people see different results.

“In web search, if you do a search for Apple, most people will get the same results. On Facebook, when you do the same searches, you get completely different sets of results because of the depths of personalization Facebook is able to do.”

It even allows you to slightly branch out from your inner circle and discover what friends of friends are into. Making your community a little bit smaller.

Say you want to find out which of your friends likes John Mayer. You input a search query, and then Graph Search cross-references the John Mayer fan page with your existing friends. Once that task is complete, you’re presented with a results page that provides the profile of each friend that has liked the John Mayer fan page. This feature works as a Big Data solution for Facebook by constantly indexing users’ preferences, likes, status updates, photos, places, etc. Which can then be recalled through user’s search queries.

There are business implications for marketer’s as well, and marketers would be smart to start jumping into Graph Search to find out exactly how the feature works.

  1. Likes = Visibility: The more likes and check-ins a brand receives, the higher your brand will be displayed on the Graph Search results.
  2. Friend Endorsements are Vital: Facebook graph Search is built on the logic of social connections and your friends’ interests. Here is a key statistic. 92% of people trust recommendations from their friends, as compared to less than 50% for other forms of advertising.
  3. Build a Local Audience: Locally based results will likely be users’ most common search queries. This means brands have the opportunity to provide value to their local Facebook fans to increase foot traffic into stores.
  4. Find Business Connections: Graph Search doesn’t mean just keeping tabs on your friends’ interests. B2B marketers can also use the feature to find connections at other businesses.

Check out the graphic below to get a visual representation of how Graph Search will work.

Why Graph Search Is Facebook’s Big Data Solution Infographic