When it comes to finding success on Facebook Ads in a post iOS14 world, there are no hacks. There is only creative.
The biggest driver in performance on the platform is having good creative that effectively communicates to your audience. But no brand, regardless of how many research studies they’ve done, comes out batting 1000 with their ad creatives.
This is why consistent creative testing is core to finding success on the platform.
But how does one effectively test new creatives in an ad account?
Can you simply develop a new creative asset once every few weeks and pop it into your campaigns and then call it a day?
In that case… how do you protect campaigns from under-performing creative?
At Thesis we’ve developed a testing methodology that generates more learnings, quicker, while also protecting our core scaling campaigns from creative flops.
In this blog post, we’ll show you exactly how we set up these creative tests and generate more creative wins for our clients.
Below is an example of the bare-bones account structure that we use for our clients at Thesis. While some brands might also have DPA campaigns or campaigns targeting additional geographical locations, this is the core set-up that we use for growing eCommerce businesses.
The foundation of our creative testing methodology is that we isolate all creative testing into its own campaign, as shown here in T_PROSPECTING_TESTING_US. There are four main reasons why we separate our creative testing from the core campaigns:
Some other things to note about this structure:
Inside of the creative testing campaign, each creative test is separated out at the ad set level. So essentially, each creative test gets it’s own ad set. We keep track of the tests by assigning them a unique number (which is simply the number of tests we’ve run) and a name that details the test.
It’s important to note that the only thing being tested in these ad sets are the elements of the ad unit itself. This is the actual advertisement that is shown to people as the browse on Facebook or Instagram. In most cases, each new creative test is testing just one element of a creative unit so that we can isolate concrete learnings. This includes:
Another important call-out at the ad set level is that we conduct all of creative testing with broad audiences. These are ad sets with zero lookalike or interest targeting, perhaps with a few guardrails on age, gender, or geolocation if necessary, but otherwise is openly targeting all of Facebook.
It’s a common belief amongst experienced media buyers that creative is ultimately what drives the targeting and the best results on Facebook Ads. But an additional reason why we do this is because we want to create the most scalable creatives possible. Since broad audiences are the most scalable (and often the cheapest), we know that when we have a creative that wins with broad, it is also likely to win in our core campaigns, regardless of the additional targeting that we have there.
Inside of each creative test, we aim to have 6 ads. This is still the number of live ads that we find optimal performance with inside of most ad sets, although this is something we should test more into.
A major perk of testing creatives with this methodology is that we’re able to jump right into iterative testing, meaning that we can test up to 6 different variants of a single creative or creative element, even if it is a net-new asset.
Under our methodology, all creative tests fall into one of these two categories:
An ideal test for a net-new video would look something like this:
Once all of that is set-up… that’s when we launch the test.
One of the perceived downsides of this testing methodology is that far fewer ad sets will be exiting the learning phase. Since many of our tests will never reach the 50 required conversions, they will likely be stuck in learning or even learning limited for their entire lifespan.
Technically, this means that performance will not be “stabilized”.
We’re making a conscious choice to accelerate creative learnings versus having the “perfect” consolidated approach. Several other top agencies also do this.
Ultimately, we’ve found that creative learnings are more valuable than consolidation… even if that means that our creative testing campaigns are often in learning.
With that said, this is something we often go head-to-head on with the Facebook team, so it’s worth pointing out that this methodology does NOT follow their best practices to a T.
Before we dive into the process for optimizing creative tests and identifying winners, it’s important to discuss how much to budget for your creative campaigns.
According to Facebook’s best practices, each ad set needs to reach 50 optimization events before exiting the learning phase. Until this occurs, the ad set is likely “to be less stable and have a worse cost per result”. So, if you wanted to follow Facebook’s best practices to a T, you’d only be able to evaluate a creative test once it’s hit 50 optimization events over a 7 day period.
Under these guidelines, if you had an average CPA (cost per purchase) of $35, then you would need to budget at least $1750 for each creative test. If you wanted the creative test to last a week, then this would boil down to a budget of $250/day.
CPA $35 x 50 purchases = $1750 / 7 day = $250 / day budget
In practice, I would say that we get pretty close to these targets. But we aren’t militant about the 50 purchases for each test, especially if we see a test performing poorly. Most times we will use CPA targets to get a rough idea of the daily budget and then optimize the test based on performance after a few days of spend.
An additional consideration is what percentage of your total Facebook Ads spend you’ll want to put towards creative testing. Every brand is different in this regard: some brands find their best performance actually coming out of the testing campaign, while others find better results coming out of their core campaigns.
Therefore, the average range varies drastically. Our clients are spending anywhere from 15% to 60% on creative testing every single month.
We typically recommend to follow the performance: if a client is driving better results from a higher % of spend in testing, that’s what we’ll do.
However, as a starting point, we’d suggest at least 20% of spend being dedicated to creative testing each month.
Once a creative test is launched, we don’t typically start evaluating results or optimizing the ad set until at least 3 days after launch. Even Facebook now suggests a minimum of 72 hours before evaluating performance to get the most accurate view of your results.
For creative testing, this allows the ad set to distribute the budget amongst the creatives, and ideally, you should start to get a sense of what kind of CPAs the new creatives are generating.
Here, we often find ourselves in one of three scenarios:
When results are looking really good, we start scaling the ad set directly in the testing campaign. We do this before dripping the new creative into the core campaigns to make sure that the creative can withstand an increased budget. According to Facebook’s best practices, you’d want to increase the budget by 20% every 3 days to avoid the learning phase.
However, depending on the temperament of the account, sometimes we actually like to increase the budget anywhere from 50% to 100% to drive learnings faster. Typically we’ll do this 2 to 3 times before identifying a winner, at which point we’ll duplicate the winning ad into the core prospecting and retargeting campaigns.
We never want to turn off an ad set that is performing well, so we’ll keep the ad set running in the testing campaign for as long as results are strong.
As results start to dwindle on this ad set, and for the creative tests that aren’t getting as good performance, we’ll take the following steps for optimization:
We use a combination of primary and secondary KPIs to tell the story of how the creatives are performing.
Since we’re a performance growth agency, driving revenue is our number one priority. So the most important KPIs we use to determine a creative’s success are CPA and the amount spent. Historically, we also used Cost Per Add to Cart as an early indicator of performance, but this metric has become less important after iOS14.
But these metrics only say whether or not the creatives worked. They don’t tell the story about why a creative performed, or more importantly, why it didn’t. To tell that story, we also track these secondary metrics to inform our learnings and create better creative iterations in the future:
While there are few downsides to this testing methodology, it’s probably best suited to brands spending at least $20k/month to ensure enough spend on the tests themselves.
When faced with a new account and pixel, typically we’d suggest starting off with creative testing to find initial wins at the ad level. Then as a next step, you can launch your core prospecting campaign to begin testing new audiences.
A detailed look at how Ad Relevance Rankings correlate with actual performance.
Inspired by a client with whom we’ve seen delivery shift dramatically away from iOS and towards Android, we wanted to see if this was part of a broad shift on the platform.