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Facebook Graph Search Taps People Power

  |  January 18, 2013   |  Comments

If the new Facebook search functionality takes off, you may have to maintain a completely different set of keywords and strategies for Bing because of its Facebook integration.

This week Facebook announced its new search functionality, "Graph Search," using Bing to power the PPC element for the Facebook search engine result page (SERP). Since the majority of you probably have a robust, well-tested campaign live in Bing adCenter already, you'll be somewhat prepared to test the advertising clicks coming out of Facebook. However, the announcement is still very important because, if the new Facebook search functionality takes off, you may have to maintain a completely different set of keywords and strategies for Bing because of its Facebook integration.

facebook-graph-search

Facebook and social networks in general are about people. People contain information, expertise, and knowledge. Traditional search engines are evolving and although the introduction of rel="author" and heavy use of Google+ are adding an element of knowledge to information, Google looks at relevance signals and calculates personalized relevance of results based on its set of algorithms, which more recently have taken into account its own version of the social graph (Google+).

How Graph Search Works

Facebook has a completely different set of information from a completely different set of users. The concept behind tapping knowledge or leading searchers to the individual that has the knowledge you seek is not new to the Internet. Quora, Yahoo's Q&A, Answers.com, eHow.com, LinkedIn's Q&A, as well as LinkedIn's endorsements, plus many other sites, all attempt to get individuals to share enough information or knowledge that an algorithm can rank them with regard to expertise and knowledge by topic. Facebook takes it a step further because it has more "signal," particularly with heavy users. In addition to knowing what you've written, or commented on, Facebook shows what you like, how much you like it, and if you've shared information on a specific topic. Facebook has indicated that the primary focus in its currently launching "Graph Search" is people, photos, places, and interests. All of these can, of course, lead to detailed knowledge about the user.

Facebook sees your behavior and that of other Facebook members every time you visit a page that contains a Facebook like button, regardless of whether you like the page/site or not. It will be interesting to see if this information will be used to flesh out your relevance to your friends' searches on Facebook for specific topics. For example, you may visit a lot of boating sites and never "like" any of them. You are still probably a great person to return in the results. But there are privacy issues because you never specifically told Facebook about your boating passion.

Unanswered Questions for Search Marketers

The personalization element of Facebook's SERP is far beyond what Google is accomplishing with Google+ integration because of the presence of greater data on member likes and greater user penetration. The unanswered questions for us as search marketers are:

  1. How much search volume could show up in the Bing-powered Facebook as a result of Facebook user adoption?
  2. How will search queries and keyword use differ when consumers are searching their social network's history, knowledge, and expertise?
  3. How will conversion rates on Facebook referral traffic differ from traditional search?
  4. Should traffic originating from a social search be treated differently, and should personalized landing pages be deployed that resemble your brand's Facebook presence more than they do a typical website?
  5. Will Bing allow for Facebook search traffic to be:
    • Turned off?
    • Bid separately?
    • Directed to an alternate Facebook URL?
  6. Should we handle "brand searches" differently in a social search environment compared to traditional search?

There are additional questions relating to a brand's organic SEO component. For example, if your brand is well liked, there might be an increased likelihood that your brand shows up in a Facebook SERP because the folks the searcher is friends with might be interacting and engaging with your content.

Risks for Facebook (Avoiding a SERP That Sucks)

The biggest risk to Facebook is that consumers start using the Graph Search to do search queries that are not appropriate for that kind of search engine algorithm. The resulting SERP might suck. Even in cases where the search query should be appropriate for Graph Search, the result might cause a SERP that sucks if:

  • The person doing the search has too few friends.
  • The query is obtuse or very narrow: "How many of my friends like extra salt on their French fries?"
  • The friends of the searcher (or Facebook members as a whole) have extremely sparse profiles: "Who do I know that works at a Chase?"
  • The question is asked in a way that requires a knowledge graph as well: "Who do I know that works at a bank?" Facebook needs to know all the banks.

At this point there is a lot of hype around Graph Search. Time will tell if it's warranted. This development does, however, raise the possibility that LinkedIn (which has much more complete profile information) might serve as an alternate place to deploy a cool graph search functionality.

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ABOUT THE AUTHOR

Kevin Lee

Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.

Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.

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