#interestbasedsearch

Can Facebook Graph Search give us the Best of Both Worlds? Can it possibly combine Google Search’s relevancy with it’s social serendipitous discoveries? Will we graduate from Content Search to Interest Search? Read on to find out..

Google has been, without doubt, the best Content Search Engine. But, it can seldom answer questions like: “How many Single Women Engineers are there in Australia” or “Restaurants in New York Liked by people from India” or “My friends who like Ice skating” ? This is the variety of questions that Facebook Graph search intends to answer.

The potential for Facebook’s new Graph Search feature is huge. Brands, digital marketers, and publishers can with it target precise groups like “CEOs in India who run marathons”.

Graph search is a friend finder, a story teller, can be a dating service and a way to learn about friends and family that you never knew about. Facebook has traditionally been more of a online catalog of online friends and family than a reliable means to expand social circles. Beyond the ‘prey on Catfish’, who among us is really seeking to meet new people on the service or make friends with strangers? Graph Search could change this limitation. There are some great things about it such as:

Facebook Graph Search is completely personalized (unique for every individual)

It’s a great Photograph search engine (where most like ones come of top)

It’s superb for Marketers, Recruiters and Interest based Search

But there are a few design flaws that need to be ironed out, such as: 

Can Find, but Can’t Discover:

Discovery is finding what you didn't know you were looking for. While we all want to be entertained, surprised, and educated, we also hate being spammed or being fed irrelevant content from loose social connections. So till the time you’re not searching “Biking Trip”, you wouldn’t know if there’s an exciting trip coming up.

So you can find, but you can’t discover stuff with Facebook Graphs.

    2. Like today, may not mean Like tomorrow:

Facebook is capturing data about what you doing right now but a large chunk of that data becomes irrelevant over a period of time. Facebook algorithm is not clever enough to judge if you really like a page or was it just sarcasm. Unlike computer code, which needs to be clear and consistent in order to run at all, human language and behavior is inherently complicated and filled with multiple, often conflicting, meanings.

Fact is that Facebook ‘likes’ and profile settings aren't necessarily accurate reflections of reality.

   3. Privacy Impossibility:

Even though users have been asked to fine tune their privacy settings, they are confused and at risk. Facebook has changed privacy settings so many times that there’s a common lagging awareness. If you haven’t taken privacy settings seriously until now, it’s time you do.

You might not mind if people specifically interested in you look at your Likes, but you may not want to have a market researcher pull the list and add it to an ad targeting profile.

Conclusion