At 3Q Digital, we’re always pushing the innovation envelope; we believe this is an essential component of success in an industry that changes so frequently. This post is part of our inaugural Innovation Week, where we showcase all manner of innovations that have improved results for our clients and teammates.
Facebook’s frequency cap is 2 for users who have not liked your Page. This makes it easy to ensure that users don’t get overwhelmed with your ads in their News Feed each day, and it also makes it extremely important that, as an advertiser, you are constantly minimizing overlap between your different ad sets.
Sometimes I hear about advertisers who think that if the same user is in the same ad set, you will start to bid against yourself. This is not the case. What happens, however, is that Facebook will begin to choose which ad gets served to that user (the ad with higher positive engagement will get served to the user).
Let’s look at a hypothetical:
Molly is a frequent visitor to Brand X, an online e-commerce site, and has liked the brand on Facebook. As a result, she is in the following ad sets: “Remarketing – all site visitors last 14 days”, “Remarketing – all site visitors last 60 days”, “Brand X Interest Targeting”, “Lookalike 1% – Top LTV Customers”, and “Lookalike 3% – Winter Product Purchasers.”
Since the Lookalike 3% is slightly further up the funnel, and is a larger audience (6.5 million users), Brand X decides to send all users in this ad set a branding post. Brand X knows that “Remarketing – all site visitors last 60 days” has the highest ROI, so users in that ad set receive a direct response-focused ad that takes them straight to a product page where they can easily add an item to their cart. Branding ads receive more engagement than DR focused ads. As a result, Facebook shows a branding ad to Molly instead of a DR ad. Molly likes the post but does not continue on to the site. Had she been served the DR focused ad, it is more likely she would have purchased.
As you can see, we have quite a few problems here. First, Molly is in four different ad sets. This makes the results less clean. It is important to keep Molly in the top performing ad set so that when she does purchase, the performance of a weaker ad set is not elevated by an existing customer. A second problem is that Molly was served the wrong ad. She should have seen a DR-focused ad but instead was served a branding ad, and the company lost out on a purchase.
With that in mind, 3Q has developed a way to ensure that there is very minimal, if any, audience overlap between the different ad sets. For accounts with multiple audiences running, we use our exclusionary pyramid:
In the pyramid, each ad set excludes the audiences above it. The idea is that the smaller, more targeted audiences don’t have any exclusions in place, while the larger, more broad audiences exclude the smaller audiences.
This allows us to ensure that users who are in the smaller, more targeted audiences are not seeing ads meant for users who are less familiar with the brand. On top of that, it ensures that the data remains clean. When there is overlap between the different ad sets, users will see and click on ads from multiple ad sets before finally purchasing. It is important that each user remains only in their ad set so the advertiser can: gauge performance of that ad set’s creative on the particular audience; see the creative that is meant for users in that ad set; and monitor frequencies at the ad set level.
If you aren’t sure which audiences should be higher in the pyramid, look at audience size. Typically, we have larger audiences excluding smaller audiences. Note: it is common for ad sets that do not have the appropriate exclusions in place to have trouble spending. This is because there is so much overlap and the frequency cap is so low, Facebook will run out of users to target if you have larger daily budgets.
There’s no time like the present to start implementing these exclusions! If you have questions as you go through the process, please leave a comment.