I am probably one of the few individuals who lives in the San Francisco Bay Area and only heads to Los Angeles during Forrester's annual Marketing Leadership Forum. I recently had the opportunity to visit Los Angeles for the second time and, just like last year, did not venture too far from my hotel. I have yet to experience the true LA "scene" or even get a glimpse of an actor, musician or sports star! But the highlight of my annual trip to LA is having the opportunity to completely immerse myself in various discussions with fellow marketers (yes, I still consider myself a marketer at heart!). Who needs to see Ozzy Osbourne'sJessica Simpson's mansion in Beverly Hills when I get to mingle with the real "stars" who are the clients, attendees, vendors and Forrester employees who participate in the Marketing Leadership Forum with such passion?
Recently we described an idea called the database of affinity: A catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter. Why are we so excited about this idea? Because if Facebook or Twitter or some other company can effectively harness the data from all the likes and shares and votes and reviews they record, they could bring untold rigor, discipline, and success to brand advertising.
But exploiting the database of affinity won’t be easy. Any company hoping to turn affinity data into something marketers can use will need three things:
Lots of affinity data from lots of sources. The raw data required to build a functional database of affinity doesn’t live in just one place. Facebook controls the most "like" data, recording more than 80 billion per month at last check. But Twitter records more "talking" than anyone else (1.5 billion tweets per month); Amazon collects the most reviews (well over 6 million per month); and Google’s YouTube and Google Display Network have data on how a billion people prefer to spend their time.
The ability to bring meaning to that data. It’s easy to draw simple conclusions from affinity data: If you ‘like’ snowboarding you might like to see an ad for energy drinks. But the real value in affinity data won’t be unlocked until we can find hidden combinations of affinity that work for marketing. That’ll require technologies and teams that can do some serious data analysis — as well as a real-time feedback loop to determine whether people really are interested in the ads targeted to them based on such complex assumptions.