Don’t mess with the algorithm: What Every Advertiser Needs To Know About Facebook’s Significant Edits
- by Brian Bowman | April 6, 2020
- Facebook Advertising
- No Comments (0)
What every advertiser needs to know about Facebook’s Significant Edits…
Don’t mess with the algorithm.
That’s the fundamental idea behind significant edits. There’s a lot more to it, of course, and we’ll get into all that, but here’s the primary reason why you don’t want to make a change that Facebook construes as a significant edit: Because it will move your campaigns into “the learning phase,” which in turn will require your campaigns to relearn and temporarily become less efficient.
The learning phase isn’t some kind of punishment. It’s built to communicate that your campaigns are being optimized by the algorithm. Once it’s triggered, you’ll see a temporary drop in your ads’ performance until the system has accrued enough data to shift your campaigns or ad sets out of the learning phase and back into optimized mode. Usually, getting out of the learning phase requires at least 50 conversions per ad set per week.
So what is the “learning phase,” exactly? Here’s how Facebook describes it:
The Learning Phase
The learning phase is the period when the delivery system still has a lot to learn about an ad set. During the learning phase, the delivery system is exploring the best way to deliver your ad set – so performance is less stable and cost-per-action (CPA) may fluctuate more frequently. The learning phase occurs when you create a new ad or ad set or make a significant edit to an existing one.
And here’s what it looks like in Facebook’s native tools:
An advertiser who doesn’t understand the principles behind significant edits could erase the benefits of any improvements they had been making with manual changes.
Here’s an example of how an advertiser could inadvertently hurt their performance:
- Say an advertiser makes five changes to their campaign over the course of 30 days.
- Each of these changes triggers a significant edit and moves the campaign into the learning phase for three days.
- While in the learning phase, the campaign may lose efficiency by 30%.
- Those five significant edits have forced the campaign into the learning phase for a total of 15 days out of the 30-day period.
- Over the course of those 30 days, the campaign has lost a sizable chunk of ROAS due to too many changes.
- The five changes the advertiser made will have to generate more than a reduction in performance to overcome the losses incurred by being in the learning phase.
Now, does that mean it’s never a good idea to go in and make a change that could possibly trigger a significant edit? No.
But it is smart to make strategic and limited changes to your campaigns. For example, don’t just try one bid strategy for a week and then switch back. Give the algorithm enough time to gather the data it needs to optimize your campaigns.
Another well-tested trick is to just leave well enough alone. Instead of changing an ad set, duplicate it, and test out your optimization changes, and see how well they work, this preserves the performance of the original ad set. While this is not recommended by Facebook’s structure for scale process of avoiding audience duplication it is viable for testing and could mean:
- You’re spending more money
- You’ve just created an audience overlap
- Your new campaign or ad set will also have to go through the learning phase too
Of course, you can always just go ahead and make the change to the existing ad set or campaign. But before you do, at least understand which changes are most likely to trigger Facebook’s significant edits.
How Facebook’s Significant Edits Get Triggered
There are four guaranteed ways to trigger a significant edit. Any changes to these campaign or ad set elements will do it:
- Bid strategy
- Optimization events
- Ad creative (including adding a new ad to an ad set)
Also, pausing an ad set or a campaign for seven days or longer will also be interpreted as a significant edit and will shift the ad set or campaign into the learning phase once the ad set or campaign is restarted.
These are changes that may or may not be interpreted as a significant edit, depending on how large the changes are:
- Switching your campaign bid strategy. This may cause multiple ad sets within the campaign to reenter the learning phase.
- Increasing or decreasing the spending limit amount of an ad set.
- Changing bid control, cost control, or ROAS control amounts.
- Altering an ad set or a campaign’s budget amount, unless you’re using the target cost bid strategy within Campaign Budget Optimization. Then any budget changes aren’t considered significant edits.
So what’s enough to be interpreted as a significant edit, and what’s not? Is a 39% increase to a campaign’s budget okay, but 41% is not? The correct answer is, “It depends”. The actual processes of triggering significant edit on the backend are much more complex and factors in many things like bidding type and spend level. Even small changes could still impact your performance. Therefore, we recommend advertisers use true budgets and cost restraints rather than treat budget and cost controls as levers for performance.
How to See Which Changes Have Triggered a Significant Edit in the Past
Concerned about how much performance you’ve lost due to significant edits and the dreaded learning phase that follows them?
You can see which changes have been designated as significant edits in your account by using the Inspect Tool at the ad set level and looking at the well-named “Significant Edit History” report.
On the Inspect Tool page, scroll down to the bottom where the “Significant Edit History” report is:
Facebook’s Significant Edits are Just Part of Increasingly Automated Facebook Advertising
If you’ve been paying close attention to the announcements from Facebook over the last few years, the principle behind significant edits should be familiar. The algorithm is increasingly taking over tasks that human UA managers used to do. And that’s a good thing.
So per the Structure For Scale best practices released late last year, the more data we can give the algorithm to work with and the less we restrict its learning, the better our campaigns will run. Instead of crunching numbers and trying to squeeze every drop of quantitative optimization out of your campaigns, we recommend you focus on creative and creative strategy.