Can Facebook’s New Graph Search be an Engine of TV Show Discovery?
Combining search with the social graph could create Social TV’s new recommendation engine
This post originally appeared on SocialTVdigest.com
This week, Facebook launched a limited beta release of Graph Search, an improvement to Facebook’s search tool. The social network touts it as a new way to search, enabling people to find information through the filter of their friends and the things they care about. If you haven’t done so already, go to facebook.com/graphsearch to get on the waitlist.
Once you get access to the beta release, you’ll be able to start searching a subset of Facebook social graph content, across four main areas — people, photos, places, and interests. Interests include TV-related queries such as: “tv shows my friends like,” “friends who live in Chicago and like Shameless,” or “people who like The Bachelor and live nearby.”
It’s important to highlight that Facebook’s vision for search is quite different from Google. A web search takes a keyword or phrase and gives you back a series of links that might be what you’re looking for. While Facebook Graph Search will strive to display a more relevant, personalized answer culled from what your friends, and their friends, have shared on Facebook.
Steven Levy at Wired writes, “The result is surprisingly compelling. 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.”
But will people end up using Facebook to search and discover new TV content that their friends are watching? And will Graph Search aid broadcasters in their goal of driving more awareness and tune-in?
It certainly might in the future, but not yet. It’s very early days and the first release is limited in what it can do. The good news is that Facebook is committed to making search a key pillar of the platform moving forward. And that will result in the social network becoming a more valuable social TV companion for consumers, which in turn will build a much richer data set for networks and advertisers. However, before that happens…
Here are 5 things that Facebook needs to add to Graph Search in order to make it a more powerful social TV recommendation engine:
1. Most social TV conversation takes place in the news feed, via real-time status updates while shows are on-air. In order to provide more meaningful results, Graph Search also needs to index user posts and status updates (Facebook has said they are working on this). Including status updates will allow the search algorithms to identify and display people who are talking about TV-related topics (instead of just surfacing people who have liked certain Facebook Pages). This is important because the TV shows our friends officially ‘Like’ may not at all represent what they’re watching and talking about right now.
2. Viewer engagement on “second screen” companion devices (smartphones, tablets) and apps are transforming the TV experience. Graph Search features need to be incorporated into Facebook mobile apps to truly leverage the growing second screen user base.
3. Apps will now be more discoverable in Facebook search results, showing up when users type something like “entertainment apps my friends use.” In the short-term, Graph Search will also evolve to integrate the actual behaviour, or actions, people take inside of apps. Netflix and GetGlue are in a prime position to benefit once Facebook adds Open Graph actions (such as, videos viewed or TV show check-ins) to its search capabilities. This will be much more valuable than just indexing that my co-worker, Ben, “likes” Arrested Development.
In the longer term, adding audio recognition technology to Facebook mobile apps (sampling audio from your TV and matching it to the show’s Facebook Page) will make it easier for people to automatically start a “collection” of their favourite TV shows. In turn, it will provide massive amounts of viewership data from Facebook users, data that networks and advertisers can eventually use for ad targeting.
4. That brings us to new ad formats. By combining social TV context (TV shows your friends recommend) and intent (new shows you’d like to watch), ad targeting can become much more effective. For example, FOX could add users who have been searching for “The Following” to its ad targeting group of potential viewers. Or, CBS could buy sponsored NFL search results that click through to show “friends in your city who like the same NFL team as you do,” offering the group the chance to win a game day VIP viewing party at the most highly recommended sports bar in the city.
As the user experience matures for Graph Search, you can bet that Facebook will roll-out enhancements to their Sponsored Result ad format and begin to monetize its new database of user intent. Once that happens, networks and brands will be able to tap into new, and potentially more effective, ad targeting options.
5. Improved search capabilities will be most beneficial to the average user if Facebook finds smart ways to add “frictionless” value. An easy way to accomplish this is to integrate search queries into Facebook notifications. For example, imagine you were interested in finding out what “new sci-fi shows my friends like” and were then prompted to turn on notifications associated with this search. That way, you’d be automatically alerted when one of your friends expresses interest in a new sci-fi show 1 month, 6 months, or even a year down the road. Now, that would be a pretty compelling feature.
Facebook’s new “search engine of discovery” is still in its infancy and currently available to only a select few. For now, focus on facilitating and creating opportunities for viewers to share and talk about what they’re watching. Before you know it, all of the fragmented TV-related Facebook activity happening in users’ news feeds will transform into the world’s largest, and most personal, social TV recommendation engine.
How do you think Graph Search will impact the Social TV landscape?
Photo Credit: bmevans80 on Flickr