Demographic profiles have long been used by marketers to segment their audience and enable them to target offers to people who are more likely to be receptive than the general population. For example, a marketer for Forever 21 might target the single, female, middle-class, age 18 to 24, college-educated demographic.
Critics of demographic profiling argue that broad-brush generalizations can only offer limited insight, and that their practical usefulness is debatable. That’s why with the mountains of data being collected about us as we surf the internet and engage with social media, some new ways of looking at targeted populations have emerged that may soon replace the tried-and-true notion of a general demographic.
But while much has been written about the “social graph” – the data from your social connections that allow you to create aggregate profiles based on who you’re friends with – we believe the real opportunity for shift lied with the “interest graph.”
Unlike the social graph – which allows marketers to understand who you like – the interest graph leverages data that actually give us a better idea of what you like. The interest graph is a better indication of your preferences than the social graph, because who you like isn’t necessarily an indication of what you like.
Interest graph data include publicly available information such as what people volunteer (e.g., Facebook interests); what people share (e.g., photos from a biking trip); who people follow; and what people say online, what they retweet and what they post. They also include “feedback loop” information from what people actually respond to, such as receptiveness to a particular campaign, which then feeds back into the database.
So how can you use interest graph data to target social ads?
1. Target followers of relevant Twitter handles.
To reach a targeted Gen Y audience, design your paid social campaign to target followers of relevant Twitter handles … and if you’re running TV ads during shows that are popular with your audience, consider augmenting these with social ads in real-time, as many viewers keep one eye on their Twitter feed and one eye on the TV screen. For example, a clothing retailer might launch a paid social campaign targeting @GleeOnFox, @Gleeks, and @GossipGirl to supplement their commercial buy during those programs.
2. Develop “personas.”
Think about how you can aggregate this handful of handles into “personas” - these represent a specific set of interests for your particular product, such as “sports car fans” or “Gleeks,” that are derived based on whom people follow, keywords used in their social streams and other publicly available keys from their social graph. To build a persona, start by identifying influencers and then add a few highly relevant keywords. For example, to use the interest graph to reach Millennials for an Emmys-related campaign, choose influencers from relevant media properties: the stars of Emmy-nominated shows like “30 Rock,” “So You Think You Can Dance,” “The Voice,” and “Late Night with Jimmy Fallon.” And use keywords like "Oscars" or "Olympics" to identify millennials who historically tweet about televised events.
The interest graph allows advertisers to target their campaigns based on these personas for higher relevance and better campaign performance.
3. Test and Iterate.
Testing interest graph-based campaigns can not only improve overall campaign performance but also help brands learn more about what interests their audiences. Plan at least one round of optimizations and prepare to learn something about your millennial customer in the process. Adjust creative to suit them as well as to keep the ad creative fresh for the real-time environment of social.
Interest graphics and personas are infinitely more valuable than demographics, because these enable marketers to better match their offers and ads to people who are actually interested. This means less wasted effort, less spammy ads and better matching … and, ultimately, better ROI.