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Posted by Nate Elliott on March 8, 2013
For years, brand marketers have guessed at people’s affinities from the barest of demographic, geographic, and contextual clues. We deduce that Midwestern men prefer pickup trucks and that people watching extreme sports like energy drinks, and then we spend billions advertising to these inferred affinities.
But today, we no longer have to guess. Every day huge numbers of people online tell us what they like. They do this by clicking a ‘like’ button, of course — but there are many other ways people express affinity: talking about things on Twitter and in blogs; reviewing things on Amazon and Yelp; spending time with content on YouTube (and telling us where they’re spending their offline time on Foursquare); and sharing things through both public and private social channels.
People’s rush to post their affinities online recalls another flood of data that began a decade ago: the explosion in online searches. John Battelle once described the data created by search as the “database of intentions,” which I’d define as “a catalogue of people’s needs and desires collected by observing their search behaviors.” In the same way, the result of all these online expressions of “liking” has created the “database of affinity,” which Forrester defines as:
A catalogue of people’s tastes and preferences collected by observing their social behaviors.
It's easy to see why people are excited about this database of affinity. Last year, Google turned the database of intentions in more than $50b in revenue for itself — not to mention countless billions more in sales for marketers. What if the database of affinity is similarly valuable?
But the database of affinity is fundamentally different from the database of intentions in several ways:
The upshot of all these differences? While the database of affinity is reminiscent of the database of intentions, marketers must use this data in a completely different way. Intent data that’s expressed just before purchase and describes a short-term need is perfectly suited to driving direct response for marketers. By contrast, affinity data that’s usually expressed after a purchase and that lasts for years is perfectly suited to supporting brand advertising campaigns.
We think the database of affinity, properly harnessed, can bring the same rigor and discipline to brand advertising that the database of intentions brought to direct response. But that’s going to require a combination of broad data, expert analysis, scalable buying tools, and ad inventory that creates brand impact. And no one company can offer that combination today.
We’re still exploring how the database of affinity will be built — and tracking how Facebook, Google, and dozens of other vendors are working to build it. We’ll publish a report on this topic soon, but in the meantime I hope you’ll join me at my speech on the topic at SXSW:
Sunday, March 10. 5pm. Four Seasons Hotel, San Jacinto Ballroom