How publishers should prepare for Facebook's Graph Search
Facebook’s new Graph Search feature could be an invaluable tool for publishers. The new search function, which Facebook introduced on Tuesday, holds promise as a way for media brands to increase their reach and improve engagement with Facebook users.
Graph Search is a natural language search engine that lets users combine phrases to find people or content that has been shared on Facebook. According to Facebook, the first version of Graph Search, now in limited beta, focuses on four main categories:
- People: “friends who live in my city,” “people from my hometown who like hiking,” “friends of friends who have been to Yosemite National Park,” “software engineers who live in San Francisco and like skiing," "people who like things I like," "people who like tennis and live nearby"
- Photos: “photos I like,” “photos of my family,” “photos of my friends before 1999,” "photos of my friends taken in New York," “photos of the Eiffel Tower”
- Places: “restaurants in San Francisco,” “cities visited by my family,” "Indian restaurants liked by my friends from India," “tourist attractions in Italy visited by my friends,” “restaurants in New York liked by chefs," "countries my friends have visited"
- Interests: “music my friends like,” “movies liked by people who like movies I like,” "languages my friends speak," “strategy games played by friends of my friends,” "movies liked by people who are film directors," "books read by CEOs"
Wired’s Steven Levy got an early hands-on taste of the new search engine and sees the potential:
“The mark of a transformative product is that it gets you to do more of something that you wouldn’t think to do on your own. Thanks to Graph Search, people will almost certainly use Facebook in entirely new ways: to seek out dates, recruit for job openings, find buddies to go out with on short notice, and look for new restaurants and other businesses. Most strikingly, it expands Facebook’s core mission — not just obsessively connecting users with people they already know, but becoming a vehicle of discovery.”
This discovery model will work for brands too. Facebook offers three tips for how businesses can optimize their brand pages for the new search tool:
- The name, category, vanity URL, and information you share in the “About” section all help people find your business and should be shared on Facebook.
- If you have a location or a local place Page, update your address to make sure you can appear as a result when someone is searching for a specific location.
- Focus on attracting the right fans to your Page and on giving your fans a reason to interact with your content on an ongoing basis.
Those tips will help you improve the Facebook equivalent of page rankings in Graph Search. The more Likes you have, the more your page will appear in search results.
But publishers should also be thinking about the ways they may be able to use the discovery engine proactively to improve engagement and build loyalty with their Facebook communities. I say “may” because it’s not fully clear yet how brands will be able to use Graph Search to learn about and target users who follow them. But here are five intriguing possibilities:
Event promotion. Querying “people who like eMedia Vitals who live in Boston” could allow us to send targeted invites to local events – conferences, meet-and-greets with editors, sponsor gatherings, etc. Adding “who work in B2B publishing” to the query would enable us to further narrow the potential audience for an event.
Deals/offers. Searching followers by interests – “music/restaurants/books/movies liked by people who like eMedia Vitals” – could enable us to promote targeted daily deals or cross-selling opportunities, directly or in partnership with advertisers.
Market research. Graph Search should be a fabulous tool for divining audience insights that can inform content or audience development programs. Inside Facebook’s Brittany Darwell notes that while businesses already can use Facebook’s Ads API for this type of research, Graph Search’s natural language processing will make it easier to frame different types of queries:
“For example, ‘pages liked by people who like Oprah Winfrey’ or ‘music liked by people who work at Facebook.’ There are infinite permutations that could help businesses determine what type of content to share with fans, what new audience to reach out to, what type of music would resonate with consumers in a commercial, who might serve as a good celebrity endorser and more.”
Community building. Finding shared interests among your “Likes” can lead to targeted content or the creation of niche communities within your broader audience.
Recruiting. Facebook CEO Mark Zuckerberg told Wired that recruiting is “one of my favorite queries.” He explained why:
“Let’s say we’re trying to find engineers at Google who are friends of engineers at Facebook.” He typed in the query and found, not surprisingly, that there were lots of people who met those criteria. Each one was represented by a little rectangle of information — their profile photo, along with snippets of key information like where they went to school, where they live, and the names of the mutual friends. … “The good thing is that there’s people at the end of these connections,” Zuckerberg said. “You can find the right people or content page and then send a message.”
Publishers could apply this to their own recruiting initiatives, searching, for example, for “friends of friends who are journalists based in New York.”
What do you think of Graph Search? Will it be a Google killer, an epic fail, or fall somewhere in between?