Facebook introduced its Graph Search feature yesterday, which allows users to search based on relationships, past Facebook activity (photos, likes, check-ins, etc.) and other data that Facebook knows about its users (home town, job, schools, etc.).
Users can search across four main categories, using a set of intuitive verbs (“lives,” “like,” “work,” etc.), nouns (“San Francisco,” “Indian,” “restaurants,” “friends” etc.), prepositions (“before,” “with,” “in”) and pronouns (“who,” that,” etc.). “Friends of friends who live in San Francisco and like Indian restaurants,” for example. Or “Friends who have been to Ireland,” or “Photos of friends before 1990.”
- John Battelle
For Google, this new service represents the organization and distribution of data that Google does not have access to. Sure Google might know your email address, that you like food blogs and the types of things you've searched for lately. However (unless you've completely filled out your Google+ profile) they don't know where you live, the name of your company, specific restaurants you like, how many pictures you are in with specific groups of friends, etc. That being said, Graph Search is not (in its current state) direct competition for Google. There is plenty of information outside of Facebook that people are looking for.
To address this, Facebook turned to its long-time search engine partner – Bing. Graph Search will pull in Bing web results if
it can't find good results within Facebook. Obviously, this is good news for Bing, but it remains to be seen if this will increase people's proclivity towards using Bing when they're not on Facebook. I personally doubt seeing Bing results on Graph Search will change that behavior.
What about traditional SEO?
The two things that fuel Graph Search have been important aspects of a good SEO strategy for years – social media activity and structured data.
Social Media Activity – Likes, Followers, Fans, etc.
For years both Bing and Google have been increasingly incorporating social activity into their search results page using Facebook and Google+ respectively. The SEO benefit is one of the reasons we include social sharing buttons where appropriate, create engaging content that our audience will want to share, and connect with fans and followers on social networks. The things you and your friends seem to like have a better chance of appearing in your search results. This still matters; it might just matter a bit more now.
Manually labeling individual words, phrases and images using microdata is not new. It's an SEO tactic that, in all likelihood, will continue to be important for some ti
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me. For traditional search engines, structured data helps Google understand how many calories are in a recipe or how many products are in stock. For Graph Search, structured data helps Facebook understand your relationship status, exact brands that you like, and where you geographically tag yourself (i.e., where you 'check-in'). The big difference, is that Facebook has easy access to structured data, since almost everything its users do from filling out their profile, tagging photos, liking brands, etc. is automatically categorized and organized whereas Google has to work for it – constantly crawling pages and requiring additional programming of sites' developers.
(Read more about microdata and SEO)
The ability to reach Facebook users based not only on their profile data (as you can do now) but also Graph Search behavior will open the door to many hyper-targeted advertising possibilities. One of the reasons that Google has been so effective at matching advertisers with an audience is its ability to predict what that audience is going to do in the future. For example, searching for recipes indicates that you might be planning a grocery run and searching for headache medicine might indicate that you need a pain reliever in the near future. While this seems fairly obvious, it is this insight into future behavior that has made Google a lot of money.
Facebook, on the other hand, has relied on past behavior for its advertising – people who check-in at their favorite lunch spot probably won't be receptive to ads for nearby restaurant, posting photos from vacation doesn't indicate the need for hotel deals and liking a brand provides more post-purchase/retention opportunities than those that increase new customers/awareness. Graph Search could change that by giving Facebook the future-focused behavioral data that traditional search engines have thrived on.
The more things change the more things stay the same
Clichés aside, many of the same SEO/Social Media priorities remain the same for brands and publishers:
- Encourage social activity by creating great, sharable content
- Use Microdata to create structured data on your own site. This will help with traditional organic search as well as when web results are included in Graph Search.
- Create and maintain social media properties that attract and engage consumers
- It might be tempting to engage in tactics that artificially inflate likes/fans through bribery, procurement or otherwise 'spammy' tactics in order to appear more often in Graph Search results. This is a short-term strategy and likely to back-fire as the Graph Search algorythm becomes more sophisticated (similar to Google's Penguin and Panda)
As Graph Search is rolled out it will be interesting to see how likes, comments, posts, profile data, Spotify playlists, etc. play a part in the results. And it gives traditional SEOs another algorithm to monitor, analyze and optimize for, which (to be clear) is exciting…at least for us.