It is a well known fact that search ads convert better than display ads. When a user searches for something, he indicates his immediate interest much better than by simply looking at a particular page.
Facebook collects tons of data on people’s interests, likes and relationships. Until recently, the only way to monetize this content was to display ads next to a person’s page on Facebook.
Enter: Graph Search. At first glance, it seems that Graph Search might be an excellent vehicle to monetize Facebook’s content. Graph Search can qualify a user better than ever since it stands at the intersection between a user’s current intent (the search terms) and his connections interests (the graph).
A number of applications can benefit greatly from Graph Search. One example is recruitment, where a recruiter may find potential candidates by narrowing down occupation, location and specific interests. Unfortunately, Facebook is not perceived as “The” professional networking tools. Its competitor, LinkedIn, is the preferred platform to manage your professional career and relations. The fact is that receiving a business requests to connect on Facebook feels like meeting your boss in your favorite bar: it’s awkward.
Another application for Facebook Graph Search is product marketing. It can be a great tool to learn more about the consumers who use your product. Finding what consumers have in common will help develop micro-marketing campaigns to cater to a specific demographic.
Those applications and many others will depend on how much data users decide to share. Facebook has an interest in sharing your personal data with other parties, but Facebookers may not like the result. How would you like your name to be the top in a result list about “people who like to get drunk”? You can find some embarrassing questions and results on Actual Graph Search Results on Tumblr. In the end, users may choose to make more data private to avoid being cast in undesirable ways.
As a new capability, Graph Search is bound to get bashed in the early stages. As it matures and we find genuine applications for this new way to search, we will add it to the toolset we use to explore the digital world around us. As more people use it, and more revenue are associated with it, one problem will eventually arise: search results rigging. Once companies understand how Graph Search is used, they will develop SEO strategies and find ways to make their results move to the top of the list. The usefulness of the results may be greatly reduced once this happens.
Written by: Gerald Burnand, CTO at Vertical Search Works `