Facebook's Graph Search: The Ultimate Personalized Discovery Engine?

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Facebook's Graph Search: The Ultimate Personalized Discovery Engine?
Facebook's Graph Search: The Ultimate Personalized Discovery Engine?

What is Graph search? Facebook Graph search is a social search feature the social company announced in mid-January. The feature is currently in private beta with a waitlist for individuals and businesses. You can join the waitlist here (scroll down to the bottom).

Facebook's announced plan is to roll it out gradually to hundreds of thousands of individuals first (English only), then more broadly for PC-based users, followed by non-English languages, and finally mobile. It's not clear how quickly this expansion will occur, but several Facebook product people are on record saying they still have work to do to figure out how to scale the computationally intensive searches across millions of concurrent users. (Think of crawling a user's social and open graph connections across hundreds of thousands, or potentially millions, of nodes for every search.) Non-trivial engineering challenges stand in the way of mass availability of this feature set.

What does it do? It really is a very cool feature. When I type in a query, such as “friends who have been to Rome, Italy,” Graph search traverses all of my relationships and those of my friends to find people who have visited Rome. It then pulls back these people and displays them alongside relevant content. This is a simple example that illustrates the difference between the kinds of results Graph search returns and how search results from Google or Bing would appear.

Another key aspect of this feature is how it appears to include implicit affinities and experiences, in addition to explicit likes and shares via Facebook. When you think about the significance of that, it's pretty impressive. Based on the content I've shared, as well as the check-ins, posts, and comments I've made, plus the images I've tagged, etc., Graph search can infer what I like, where I've travelled to, and a myriad other things about me. The inclusion of implicit affinities is only possible due to Facebook's massive scale and could ultimately be the component of Graph search that makes the results valuable enough to get people to use the feature.

What is it good for?

  • People search: Finding people you're connected to who have specific interests and experiences.
  • Local (and vertical) search: Finding a business and/or events that friends have visited and/or liked.
  • Media and entertainment search. Finding TV shows, movies, music, and games liked or watched by your friends.

Will consumers use it? At the end of the day, this is the most important question. If consumers embrace it, Graph search has the potential to transform search signals and lead to the dawn of discovery marketing. But that's a big “if.” Historically, consumers have been trained to turn to the search engines for this. Changing consumer behavior is notoriously difficult to do.

Where I think this is possible is on mobile devices. Industry research suggests that many consumers turn to specific mobile apps to conduct vertical searches. For example, I use Yelp to find restaurants, the Weather Channel app for local weather, and Google Maps for directions. It's in the app environment on mobile devices where I think Graph search has the greatest potential to reach critical mass and experience rapid adoption. It's unclear when that will happen, but it's doubtful it will be available for mobile devices in 2013.

How will Facebook monetize it? Facebook hasn't yet announced how it will monetize the feature. The obvious opportunity is to charge for sponsored listings, much like AdWords. There are also a few other options, including:

  • Syndicate aggregated data to advertisers. Data would show what people are searching for, and who or what they're finding, etc.
  • Creation of premium audience segments for targeting across the network via the FBX.

What does it mean for brands and publishers? It's going to take some time (several months at the least) for the feature to achieve critical mass. I don't anticipate Graph search will be something brands or publishers will be investing in directly in the first half of this year if for no other reason than monetization of the feature is one of the things still being figuring out.

What should digital marketers and publishers do about it now? The potential for the feature is huge. Brands and publishers can and should be doing a number of things right now to benefit from it as it reaches critical mass. A simple rule of thumb is that the more content that gets shared, liked, or commented on through Facebook, the greater the chances of discovery of that content through Graph search.

Actionable insights. Here are three things brands and publishers can do right now, which are in accordance with best practices:

1. Enable and encourage social signals (shares, comments, and likes) within your content.  Shares, likes, and comments appear to be significant drivers of Graph search results.

2. For certain brands and publishers, it's important to enable and encourage image sharing.  Images are the single most popular type of content to be shared on Facebook. It stands to reason that images are something people will search for a lot through the Graph.

3. Deploy Open Graph tags within content. These will ensure consistent “merchandising” of brand/publisher content that gets discovered through Graph search.

More background and reviews. All of the reviews I've read range from lukewarm to effusive. It really does seem like Facebook is onto something big with Graph search:

Ben Straley is vice president of social technologies at Rio SEO and Covario.

DMNotes is DMN's around-the-clock blog. Yes, a blog in 2016.

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