Audience Optimization is a new tool that reveals the hundreds of thousands of categories Facebook divides its users into, but also the number of people who belong to each one. The tool allows any official page manager to identify the “Preferred Audience” for a post by searching for and selecting interests relevant to the story. To help make sure these interests are just right, i.e, not too niche nor too broad, Facebook auto-completes interests and displays the total audience size for each one. This is not as a subset of your page’s followers, but as a subset of all Facebook users. Most interests are sorted into broad categories like Lifestyle and Culture, People, or News and Entertainment. It is the closest complete, ranked list of every interest on Facebook.
Facebook says there are 839 million interested in love and 571 million in happiness. These are larger compared to the 88 million interested in categories like the 28 million interested in envy, 41 million in crying, 81 million in boredom and 88 million interested sin. These categories and interests are formulated algorithmically from popular Facebook open graph pages (the articles, music, and videos being shared), Facebook Ads tags, and other Facebook data sets. The list suggests that the algorithms are scraping keywords from people’s posts. (Facebook says Messenger was not included.)
If you want more info, take a look at What the Verge did: they created the top 10 biggest audiences in a few categories: celebrities, 2016 presidential candidates, positive and negative emotions, gadgets, and a sampling of the most bespoke hipster interests with fewer than 30 followers. Note that audience size does not take into account sentiment. So just because Donald Trump has 20 million may not mean it’s all positive or flattering. They have extracted the top 2,001 interests here, or you can download the exhaustive 18.2 MB list. They even made an interactive Facebook popularity quiz.
These lists show us what Facebook is learning about people who post there. Facebook was clear that Preferred Audiences are not (necessarily) the same as its advertising tags. However, but they both rely on similar algorithms to sort users and target us with content. So if you are wondering why you see certain ads, this may help to explain some of that. Will this be helpful or hurtful to agencies? For marketers, this could be very helpful in target marketing. As a regular person, be careful what you post. You’ll probably see more of the same; these platforms we all use are definitely into collecting our data.
@DrNatalie, VP and Principal Analyst, Constellation Research
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