Learn how budget optimization, objectives, optimization goals, and bidding affect performance
Understand whether the learning phase and ad quality have an impact on your account
Discover the best time and day to launch your ads
Madgicx Auction Insights gives you an instant overview of where your ad budget is being spent, with data overviews of:
Placement and device
Budget optimization method
Ad quality ranking
Head to 360° Meta Audit and look for Auction Insights in the menu at the top of the page. As always, set the time frame that you want to see data for. And just like the other tools in Madgicx, you can filter the data to see performance per campaign, status, funnel stage, and more.
Analyze performance by device and platform 🔬
The placement and device widget shows you exactly where your ads perform best: on which device, what operating system, and which placement.
☝️For the account in the screenshot above, we have left the metric as “ROAS” and can see the performance across devices and systems more or less corresponds to the spend:
Mobile outperforms Desktop with a ROAS of 6.07 which has increased by 16% compared to the previous 30 days (that’s the date range selected at the beginning)
iOS has increased ROAS by 30% compared to the previous 30 days and is now 12.06.
The Stories placement performance has dropped when compared to the previous 30 days, and Video only has improved by 103%.
You want the spend and revenue percentage to be as close to each other as possible and allocate budgets away from the poor-performing device/system to the one performing better to reach this spend-performance equilibrium. In the above example, we may think about slightly reducing the budget for desktop to get even closer to this equilibrium.
In the above screenshot, we have switched to the “Breakdown View”. Here we can see which placement is performing best in terms of spend to ROAS. We can see that our Instagram Feed on iOS has the highest spend, but not the best performance. The top performing placement is Facebook Stories on iOS, but the spend is second to lowest in this view. Based on what we see here, we may look to shift some of the spend towards this better-performing channel.
Now we need to take a look at how this budget is being optimized.
Understand your budget optimization 🤓
While it is a hot topic amongst media buyers whether advocate for optimizing budgets on ad-set level or campaign level, you need to know what works for your account. There are advantages and disadvantages to ABO and CBO that you should consider, but you need to consider how each works for you.
In the Campaign Type & Budget widget, you can see which type of budget optimization is working best for your ad account.
☝️For the account above, we can see at a glance that campaign budget optimization (CBO) is outperforming ad-set budget optimization (ABO).
For our future campaigns in this account, we’ll bear in mind the fact that CBO crushes it compared to ABO. However, it's important to filter results by funnel stage because different budget optimization methods could work differently for acquisition and retargeting, for example.
In the “Campaign Objective” and “Ad Delivery Optimization” widgets, we can see which campaign objectives and ad delivery optimization goals work best for our account.
Here at Madgicx, for example, we have noticed that using Conversions campaign objective delivers unbeatable sales and ROAS for eComm businesses.
The same thing goes for Lead Generation businesses, which typically see the greatest success with Conversions and Lead generation objectives. But keep an eye on Facebook releasing new campaign objectives, such as Leads for Lead Generation and Sales for Ecommerce businesses.
Other objectives might bring lower CPMs and Cost per Click, but will bring low-quality traffic, wasting your budgets and hurting your pixel data, which will result in bad lookalike audience performance.
☝️ For this eCommerce business, we are rightly focussing mostly on conversions and our bottom line, with some budget allocated to nurture via lead generation.
Now let’s take a look at how we are optimizing our bidding: are we trusting the algorithm or do we know better?
Optimizing our bidding strategy can have a notable impact on results.
☝️ In the screenshot above, we can see that we are trusting Facebook’s “Lowest Cost” (now called “Highest volume”) strategy, without limiting the amount that can be spent for over 90% of our budget. This strategy aims to get the most results possible from our ad budget.
As a general rule, using automatic bidding is recommended when you're just starting out. However, if you already have some experience and know how much your conversions usually cost, you can start experimenting with manual bidding. We can see that the account above has added a "Cost Cap" manual bid for the remaining 9% of spend, setting a maximum bid across auctions (rather than allow Facebook to bid dynamically).
Assess Learning Phase results 🎓
“The learning phase is the period when the delivery system still has a lot to learn about an ad set.” Meta Business Help Centre
Reading the quote above, you’d forgive advertisers for being afraid of resetting the learning phase if they can avoid it. But we’ve found that this sometimes causes you to miss out on scaling opportunities
The “Learning Phase” widget makes it easy to answer whether it is worth you waiting for the algorithm before scaling ads.
☝️ In the screenshot of the account, we can immediately see how the ad sets in learning outperform the ad sets that are out of learning by a long way.
If you see that ad sets “in learning” or “limited learning” are outperforming those that are out of learning, this mostly means the learning phase isn't the decisive factor in dictating performance in your account.
It doesn't necessarily mean it's better for your ad sets to remain in learning; just that other factors are more important.
The idea here is that you shouldn't be afraid to make changes to ad sets out of fear of the learning phase and miss scaling opportunities. It's not necessarily that you need to keep the ad sets in the learning phase and scale while they’re there, but that you need to scale regardless of the learning status if your ads are performing well.
Benchmark your performance 📏
A ton of advertisers take engagement, conversion, or quality ranking as the gospel truth and spend hours and days optimizing each of these metrics.
Madgicx gives you a quick breakdown against Facebook’s benchmarks to see if optimizing according to these rankings is really worth it.
If you're not happy with an ad's performance, the quality ranking may hint at what's wrong with it and what you can improve. If your performance is great, however, there's no need to pay attention to these ad quality metrics.
👇 In this account, you can see that Facebook’s ranking and actual performance don’t always correlate.
As you can see above:
Averagely ranked engagement is churning out almost twice the ROAS as above average
“Bottom 35%” conversion ranking near doubles the performance of the average
The bottom 35% in the quality ranking blows the above average (top 45%) out of the water by over 10x
This data just goes to show that you can’t take Facebook’s assumptions at face value. You need to dig into the data and see what works for your individual ad account and business.
Compare ad-type performance ⚖️
The Ad Type widget helps you identify your best ad types and compare their performance based on the KPIs selected in the specified time frame.
The different ad types include:
DCO (Dynamic Creative Optimization) ads
MTO (Multiple Text Option) ads
DPA (Dynamic Product Ads)
This widget allows you to compare performance among different ad types — mostly normal ads vs. DPAs (Dynamic Product Ads).
We can see from the above screenshot that DPA is killing it in terms of ROAS over this timeframe.
Get granular breakdowns 🌾
Auction Insights also allows you to see how your ads do by the hour on specific days. For example, this data can help you know which times to set up automations to pause ads for certain times on certain days.
☝️ In the account above, we can see that over the past 90 days, the ad performance drops between 01:00 and 07:00. So we may look to pause the ads for this time.
If we hone in on Sunday, we see it is the worst performer of the week. We could turn off ads for Sunday, or pause them for the worst-performing hours of that day (from around 01:00 till 10:00).
Frequency and reach are two important factors in marketing campaigns. For example, a higher frequency might help drive ad recall or influence a purchase decision, while a lower frequency keeps ad fatigue away.
Understanding these factors can help advertisers define the right frequency level when planning their next ad campaigns.
Use the Frequency Breakdown widget to see if you are either bombarding existing audiences too much and not reaching new pockets, or reaching too many new people and not doing proper remarketing.
You want your first-time view reach to be the highest and then for this number to tail off to those that you want to retarget. Facebook will distribute ads to the same audiences in waves to increase the touch points of the ads and brand awareness to drive purchases.
Facebook Ads Manager
View per ad set
Aggregate view of performance
Can’t compare performance on an hourly basis
No CBO/ABO performance comparison
CBO/ABO performance comparison
No performance comparison of learning-phase stage
Learning-phase stage comparison
No performance comparison of automatic bids against manual bids
Automatic vs manual bid comparison
Facebook-ranking results companion
Frequently asked questions
Which Madgicx plans include Auction Insights?
Madgicx All-in-One (with and without AI) and Madgicx Insights (with and without AI).
How can I save a specific view?
Save specific data views by clicking the “Filter Data” button in the top left corner, setting the parameters, and then clicking the “Save this View” button, entering a name for it.
The KPI that I want to select is not available. What should I do?