What I’m about to show you is a trade secret.
It’s the result of hundreds of gruelling hours spent running thousands of campaigns, and optimizing them to exceed the expectations of the most demanding brand marketers in the world.
Regardless of campaign objective, we promise this approach will help you create better Facebook strategies that will exponentially improve your results.
Introducing Facebook Audience Insights (your new secret weapon)
In May 2014, Facebook released a tool called Audience Insights to help brands better understand their audiences. With this feature, brands can break down specific audiences, like users who like their brand on Facebook, the general population on Facebook, and users within specific sub-segments of custom audiences (Leads, Purchasers, Cart Abandoners, Foot-Traffic, etc.)
After choosing an audience set, you can then break down this data into a variety of categories:
- Demographics: Age and Gender, Lifestyle, Relationship Status, Education Level and Job Title
- Page Likes: Top Categories of Page Likes, Most Relevant Pages by Affinity
- Location: Top Cities, Top Countries and Top Languages
- Activity: Frequencies of Activity on Facebook including Device Usage
- Household (US Only): Household Income, Ownership, Size, Market Value and Spending Methods
- Purchase (US Only): Retail Spending, Online Purchases, Purchase Behavior and Automotive Purchase Behavior
How this will help you truly understand what interests your audience
This tool is a goldmine for effective campaign planning.
If we asked a few of our employees what they thought AdParlor’s ideal prospects were interested in, they’d likely guess AdWeek–and they’d be correct– but what else? We were surprised to learn that in addition to AdWeek, they were also interested in:
- News & Media: TED, Refinery29, TechCrunch, NowThis, New York Magazine, Delish, Thrillist, Food Network, PBS, Forbes, Business Insider, Inc Magazine, Tasty, NPR, Mashable & more
- Politics & Personalities: George Takei, Barack Obama, Hillary Clinton, Bernie Sanders, Elizabeth Warren, Ellen Degeneres, Michelle Obama, Bill Maher, Dalai Lama, Dan Rather & more
- Product, Services & Companies: Facebook, YouTube, iTunes, Spotify, Southwest Airlines, Funny Or Die, Disney, Starbucks Whole Foods, Netflix & more
This means that not only can we target users based on their interest in AdWeek, but we can also leverage similar interests to increase our scale and relevancy.
From here, our team can take this insight and use interest-based targeting groups across all publishers to be efficient in our targeting.
Some of these we might have guessed, but the majority wouldn’t have been anywhere on our radar.
So what happens when you test this in-market? When comparing campaigns that have been informed by Facebook’s Audience Insights versus general interest-level data, we’ve seen increases of 11.89% in ROAS and reductions of 10.07% in CPA.
The proof is in the numbers.
How to use this information to inform your creative
On top of identifying better targeting, you can also identify creative trends from Audience Insights data.
When collecting a variety of interests, lifestyles, demographics and activity-level data, you can also collect Creative Insight data to test against. Let’s take a look at AdParlor’s Audience Insights information.
When breaking this data down for our own site, we identified a few interesting trends:
- Age Breakdown: 50% of our audience are ages 18-34, with 29% of the total audience falling in the 24-34 age bracket
- Interest Breakdown: The top interests from users who like the AdParlor brand are Facebook Business, Verizon, Nasdaq, Amazon.com and Tasty. Our users tend to like tech-relevant brands & businesses
- Education Breakdown: 67% of users who like the AdParlor brand are College-Educated, according to the Audience Insight-level data
- Job Title Breakdown: The highest relevant job titles from users who like the AdParlor brand are from IT & Tech, Computer, Media and Business
This is a lot of information to unpack. However, it is easy to extract some of the common themes and trends from this data. To drive sign-ups, we could use the data to create the following sponsored posts:
The above mockups are inspired by data trends that we’re seeing. We featured a younger model since 50% of our audience falls in the 18-34 age bracket. Because our users express interest in tech-relevant brands and businesses, we featured the model using technology in the imagery. Finally, because of the high relevancy to tech / marketing jobs, we wanted to ensure that she was in an office-space that looked modern and tech-driven.
There are many more characteristics that we can derive from this data to produce creative. So instead of dedicating resources to produce creative assets you’re unsure about, you can use this data to inform what your ads should look like.
Have more you want to discuss? Reach out to us on Twitter and we’ll reply with even more ideas on how to apply this strategy for your paid social media campaign.