Social Media as The Database of Affinity

Group of Business People with Infographic Illustration Above Them

On June 23, 2014, Erika Brookes from Oracle and Nate Elliot from Forrester Research touched on a very serious issue – how to remove the noise from social media listening in order to find the signal: what the market is saying about your brand. It is all about affinity, or as Forrester defines it:

People’s preference for – or desire to connect with – other people, products, or things.

How do people express their affinity? According to Nate: liking and voting (137 billion Facebook likes and 36 billion Instagram likes per month) and talking (15 billion tweets per month and 38 million WordPress blogs per month). Not to mention Amazon and Yelp reviews, billions of hours of YouTube content, nearly 200 million Foursquare check-ins, let alone sending email. We like, or need, to connect with those who have or share related viewpoints. This social need bleeds over into what we think and say about the brands we choose.

The end result of this inherent need is a whole lot of data, which includes variables that have predictive power. For example, researchers at Cambridge University used Facebook likes to predict personality. Chances are if you like “The Daily Show” you are more likely to be liberal.

Just over ten years ago, John Batelle coined the phrase “Database of Intentions”, which at the time arose from the rise in online search. Therefore the Database of Intentions is a catalog of people’s needs and desires, as collected by observing their search behaviors. This thinking can be applied to social media behavior in the form of a Database of Affinity: a catalog of people’s tastes and preferences collected by observing their social behaviors. Of course, Google (as a driver of the Database of Intentions) outperforms Facebook (as a driver of the Database of Affinity) several times over if you compare their respective revenue streams.

Although both forms of data are valuable to marketers, they are fundamentally different. They capture moments of expression at different points in the customer journey. The Database of Intentions captures data prior to the moment of purchase. It is a rational process created through exploration; it is of limited duration; it provides benefit to direct marketers. In contrast, the Database of Affinity is observed through social behavior, it involves an engagement process that is more emotional than rational, the duration of effect is longer, and is of most benefit to brand marketers.

In short, the majority of social media likes and conversations are coming from existing customers. It is not the same type of pre-purchase data that one sees from the Database of Intentions. In fact, it is proposed that the Database of Affinity will bring the same measure of discipline and success to brand marketers that intentions have brought to direct marketers.

To actualize the wealth of affinity data, marketers will need a broad slice from all of the observed social channels, processed by a suite of analytical tools that allows researchers to conduct sophisticated searches for cross-affinities. Finally, marketers will need online ad formats that are robust and rich enough to allow for meaningful ads – not just the flat, text-based ads which are still common on social sites. The direction Forrester sees the market going is toward “Smart Affinity”: marketers will have access to comprehensive data, tools robust enough to yield meaningful analysis, and ad platforms that will provide high impact ads.

Shouting out the voice of the customer through market research, analytics, and strategy with a bit of distinctive flair, Greg Timpany (@DataDudeGreg) directs the research efforts for Global Knowledge in Cary, North Carolina, and runs Anova Market Research.

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