It is time to rethink how we manage Facebook advertising campaigns, and Facebook has a new framework to do it with: Structure for Scale. Learn how to prepare for automated media buying within this new framework.
Facebook’s Structure for Scale: How to Prepare for Automated Media Buying
Structure for Scale is designed to optimize campaign setup and management in a post-AI advertising world. Basically, it’s a set of best practices advertisers should adopt if they want the Facebook advertising algorithm to operate at peak performance.
Best practices for Automated Media Buying
Reducing the number of campaigns and ad sets to prioritize quality over quantity
- Setting campaign optimization budgets (CBO) so each ad set can achieve 50 unique conversions per week
- Moving optimization events closer to the beginning of the sales funnel
- Reducing changes so campaigns and ad sets spend less time in the learning phase and move to the optimized mode
- Increasing reach and minimizing audience overlap so the algorithm can more efficiently find conversions, and thus has enough data to further calibrate and optimize all other campaign settings
- Bidding aggressively enough to maintain delivery
- Using creative asset customization and auto placements to let the algorithm figure out what works best
If you pay close attention to Facebook advertising and the announcements and best practices they publish, you’ll remember the Power5 recommendations they announced this summer. Structure for Scale has a lot of similarities to the Power5 best practices, but it is a further evolution or iteration of how to run Facebook ads right now.
It also appears to work. That might seem like an odd thing to say, but we sometimes hear advertisers express suspicion about the best practices Facebook recommends. There is a sentiment of “well, using those tactics may be best for Facebook, but it’s not necessarily best for me.”
Facebook is building up a library of case studies to dispute the naysayers. You can review several dozen different examples of how effective the Structure for Scale best practices are.
Here are just a few examples:
- The National Holistic Institute applied Structure for Scale by consolidating their account’s ad sets and turning on campaign budget optimization and automatic placements. It got them a 77% decrease in cost per lead, 4.9 times more leads, and a 230% increase in school enrollment.
- Bombas simplified its account structure and got a 2x increase in purchases.
- Mino Games simplified its ad campaign structure and ran Facebook video ads with automatic placements. This increased installs and in-app actions, earning them a 90–95% higher average revenue per player on day 7.
- Jet.com expanded its placements to Facebook, Instagram, and the Audience Network. That got them a 334% lower cost per purchase and an 86% lower cost for traffic on the Audience Network.
The Key Principles Behind Structure for Scale
So the benefits of Structure for Scale are clear. Here’s how to apply them to your own account or to your clients’ accounts.
Simplify Your Campaign Structure
This is a recommended best practice you may have heard of before, but it’s at the crux of this new approach to Facebook ads.
Basically, Facebook wants you to KonMari your campaigns and ad sets. To go from this:
Why? Because it gives the algorithm more room to learn and efficiently optimize.
To work well, the Facebook advertising algorithm needs the correct amount of data to crunch. This is core to how machine learning works, and it’s a concept you must grok if you want to advertise successfully now and in the future.
Before we had an algorithm to manage campaigns, it made sense for human ad managers to create many (sometimes hundreds) of campaigns to control all sorts of variables – bids, targeting, audiences, placements. This lets us test settings, isolate audiences, and manage many other levers of campaign management.
But now that the algorithm manages so many of those things, creating lots of campaigns just gives the algorithm less data to work with. And with less data, it doesn’t work as well.
To understand how the algorithm works, it helps to know which data signals it’s working off of. These are just a few of the ones used for the type of goals an eCommerce site might use:
- Ad engagement or video viewed
- Add to cart actions
- First day on brand site before purchase
- Purchase device
- Number of pages viewed each day on brand site
- Number of days on brand site before purchase
That’s some very detailed information. When you create a lot of campaigns, you’re basically putting a blindfold on how much data the algorithm can use from campaign to campaign to optimize your ads. As a result, campaign performance gets crimped.
Facebook is calling for advertisers to increase “liquidity (flexibility) by removing constraints” on their campaigns. One of the constraints to be removed is to open up your account structure by minimizing how many campaigns and ad sets you have. Another way to improve “flexibility” is to use Campaign Budget Optimization to free up how your ad budget is spent. And yet another way to give the algorithm the flexibility it needs is to allow it to pick ad placements so it can test your ads across the 14 different placements available.
This means, of course, you will be giving up lots of control. Some advertisers do not like that. But here’s how Facebook views this “control” versus “algorithmic optimization” quandary:
Which would you want? More conversions, or more control? Personally, if I could be assured the value of those conversions is as good as what I was getting before, I’d go with more conversions.
But what happens if you can’t cede control? Your ads will stay in what’s called “the Learning Phase” or “Ad Set Calibration” longer because the algorithm can’t crunch data in the way it was built to do.
Staying in the Learning Phase for any longer than necessary is not a good thing. It suppresses return on ad spend by anywhere from 20-40%. To shift out of it, each ad set needs to generate approximately 50 unique conversions per week and to stay out of it, advertisers need to not make any “significant edits.”
So as we walk through each aspect of Structure for Scale, understand that the overarching principle here is to remove limitations on the algorithm in order to gain conversions. This means setting campaigns up in a way that allows the algorithm to do its work, and to minimize tinkering with the system once it’s running, lest you trigger any “Substantial Edits” that force the algorithm to recalibrate again.
Ultimately, Facebook just wants you to adjust a few key levers so the algorithm can do its job.
Automated Media Buying
Lever #1: Increase Audience Size
Facebook recommends four ways to do this:
- Increase retargeting windows. Many advertisers have tight windows, like one to seven days. That only works if you have substantial website traffic. So, to expand your audience and give the algorithm more room to work, try increasing your retargeting window and see if you don’t get better results.
- Merge your Lookalike audiences into larger groups. Facebook recommends 0-1%, 1-2%, 3-5%, and 5-10%.
- Group interest and behavior targets with high overlap together. Just make sure the creative strategy is the same for the groups you’re merging.
- Minimize the audience overlap. Get smart about audience exclusions, including screening out past purchasers.
Lever #2: Combine Placements
Facebook has 14 ad placements across its family of apps right now. Trying to manage that is complex, to say the least. It’s really better to let the algorithm manage placements, especially when you add in other performance factors like ad sizes. So select Automatic Placements and turn your focus to other things, like doing competitive analysis or enhancing your creative strategy.
Still don’t want to give up control? Then consider this: Facebook says shifting to automatic placements reduces the cost per conversion by 71%. That’s an awful lot of freed-up ad budget. And if you just really must have control over where certain ads appear, use “Asset customization.” It will let you choose which images or videos people see in your ads depending on where your ads appear.
Lever #3: Increase Budget Liquidity
Here are a few ways to give the power of the purse strings to the algorithm. Because even if you minimize control on every other aspect of campaign management, without freed-up budgets, the party can’t really get started.
- Increase budget-to-bid ratio. Calculate your daily budget based on the 50 conversions per week threshold needed to get out of the Learning Phase. So if you want to pay $1 per conversion, set your budget for at least $50 a week (probably about 10-15% higher because bids usually end up being that much higher than what you’ll actually pay).
- Use Campaign Budget Optimization. As Facebook says, “Free the budget!”
- Test creative at the ad level. Don’t create multiple ad sets, each with one piece of creative, and then run the ad sets against each other. Put the different pieces of creative all within one ad set.
Lever #4: Bid High Enough, and With the Right Strategy
The days of human-managed bidding are over. It’s vastly better to let machines manage the complexities of changing bids. But choosing a bid strategy is still best left to humans… if humans take the time to think about it carefully.
Facebook breaks out three types of bid strategy:
- Lowest cost. Want maximum conversions from your budget? Then pick the lowest cost. Use this especially if you don’t know lifetime value.
- Target cost. This gives a cost per result on average. If you want consistency, go with the target cost.
- Lowest cost with a bid cap. Got a broad audience that’s not as likely to convert? This is a good option to control costs. Or, if you are willing to spend up to a certain amount for a given conversion, but no more… then choose the lowest cost with a bid cap.
Two extra pieces of advice:
- If at all possible, bid according to lifetime value. It makes no sense to bid like all your prospects are created equal. They aren’t.
- If you are using a bid cap, make sure that the cap is high enough. Otherwise, you’ll be severely limiting how often the ad gets shown, and thus you’ll be limiting the amount of data Facebook gets to work with, and… you know the rest.
Lever #5: Optimize for the right event
For niche or higher-value products with fewer purchases, try moving your conversion event up towards the beginning of the funnel. This usually gives the algorithm more data points to work with because for every step of the funnel toward the purchase, there are fewer conversion events.
Here’s how this can work: When we first launch a game/app, we’ll optimize for App Installs. These clearly, aren’t as valuable as purchases, but if we haven’t generated enough purchases (or aren’t generating enough purchases) we can optimize the overall system much faster by focusing on App Installs. As soon as we’ve got enough App Installs to move down the funnel, we’ll optimize for App Events like a purchase.
Facebook Advertising: Past, Present, and Future
Facebook and Google have made major strides in the last year towards simplifying and streamlining their ad platforms. This is overwhelmingly a good thing because of:
- Allows more people to effectively use the platforms, regardless of their advertising skills
- Saves ad managers’ valuable and very limited time
- Gets better results
However… if you’re an experienced, proactive, and performance-driven advertiser, letting go of all that control is tough. It means completely rethinking how you advertise. It may also mean updating your skills in automated media buying because the algorithm can do a lot of Facebook ad management tasks better than people can now. We recommend you switch how you spend your time over to creative strategy and competitive analysis.
For a more detailed view of preparing for automated media buying, click here.