Can what you "like" on Facebook reveal your personality? A team of Cambridge researchers attempted to answer that question in their paper entitled "Private traits and attributes are predictable from digital records of human behavior," and they found that race (African American vs. Caucasian), religion (Christianity vs. Islam), gender, and political views could reveal your personality with 82 percent to 95 percent reliability.
But why? When people choose to "like" something - or choose to pass on "liking" something - they consciously or subconsciously consider their own personal brand. In other words, when you "like" travel-, hiking-, or snowboarding-related pages, you do so because it is "on-brand" and reveals a bit about you. Now imagine for a moment looking at this data across a pool of people (perhaps those who have "liked" your Facebook page) to create a visual map of who your fans really are. How about taking the process one step further by performing an analysis to get a set of personas - distinct personalities of people who associate themselves with your brand. Well, it is possible and the results can be magical in both validating traditional personas that may already exist, and/or uncovering surprising new consumer segments you never knew existed before.
How? By leveraging the power of the community.
It starts with the data, but requires a commitment to analyze and act on that data. Today's leading brands generally find themselves well-positioned to collect the enormous data and insights available via their social communities. More often than not Facebook Connect, social sign-in, or multiple applications that include an app acceptance process to gain access to special content, contests, or coupons have been implemented. While these initiatives often provide great value to the community and keep them engaged, they also enable the brand to ask for and gain access to critical insights about the individual, including location, interests/likes, birthday, and more during the authentication process. With trusted brands that provide value and transparency to the consumer, app acceptance rates, and therefore access to this data, can range from the 50 percent to 80 percent range.
The next step is to analyze the data. No easy task, as unstructured data such as interests can be a bear to process and should generally be left to specialists who have built solutions that can provide compelling ways to best present that data such as visual maps around affinities. Once affinities that leverage likes and interests are understood, a deeper analysis can be conducted to understand what makes them different. Traditional or proprietary clustering algorithms may be used to detect distinct segments across the fan base that can then be compared and contrasted to a brand's existing segments. Once defined, these insights can then be used to inform, craft, and/or refine the brand's digital marketing strategy and tactics. Common uses include:
Measurement and analysis is a growing yet still very much immature aspect of social media - but it is rising in importance quickly. In fact, in a recent report by Forrester analysts Nate Elliott and Zach Hofer-Shall, the duo predict that measurement will emerge as its own category of social technology over the next two years. Why? According to Elliott and Hofer-Shall it's "because savvy marketers will demand social measurement tools that demonstrate how their social programs are creating marketing and business success."
Leveraging social data to find new consumer segments creates exciting new opportunities for brands (for more information, check out this blog post). However, supporting those segments with the right content partnerships and sponsorships to create engaging content is critical to growing and nurturing those segments. In the end, that is where brands can create real marketing and business success over the long term.