We often see advertisers trying to optimize their ad placements based on ACOS for each placement type. It seems logical at first. Lower ACOS typically signals better performance, so why not increase bids there at the placement level?
Here's the thing: placement modifiers can only increase your keyword bids. They're not independent, and there's no default CPC that exists on its own for a placement.
In other words, you can't separate placements from keywords.
Let's look at a real example to illustrate this:
At first glance, you might think: "Rest of Search and Top of Search have nearly identical ACOS (38.8% vs 38.9%), so they should get similar adjustments. And Product Pages at 82.3%? That's terrible, let’s definitely reduce it to 0%."
But here's where ACOS-based logic falls apart: if you were only looking at ACOS, you'd think Rest of Search and Top of Search should be treated the same. Yet AdLabs sets Top of Search at 90% while Rest of Search gets 38%. More than double the difference!
The proper way to optimize placements is based on the relative conversion rates (or more specifically, Revenue Per Click) between placements.
Here's the key principle: The placement with the best conversion rate deserves the most aggressive bidding, regardless of what its ACOS looks like.
Look at the data more closely:
Top of Search: 25.4% CVR, $6.19 RPC (best performer)
Rest of Search: 22.9% CVR, $4.52 RPC (second best)
Product Pages: 14.7% CVR, $3.26 RPC (worst performer)
Even though Rest of Search and Top of Search have nearly identical ACOS, Top of Search converts at 25.4% with $6.19 revenue per click, significantly outperforming Rest of Search at 22.9% CVR and $4.52 RPC.
Product Pages has the highest ACOS (82.3%) and the lowest Revenue Per Click ($3.26) with the worst conversion rate (14.7%). That high ACOS is simply a result of poor conversion performance.
Here's an important insight: your target ACOS doesn't change how you calculate placement adjustments.
Whether your target ACOS is 30%, 15%, or even 100%, the optimal placement adjustments remain the same.
Why? Because placement adjustments reflect the relative performance differences between placements, not your overall ACOS target.
So if placement adjustments don't control your ACOS, what does?
If you reduced placement adjustments to try to lower ACOS, you'd run into two issues:
You'd lose the ability to control the relative CPC for each placement based on the conversion rate
All placements could end up at 0%, and you might still be above your target ACOS
AdLabs adjusts your base keyword bids instead. Placement modifiers then scale up from that base bid according to their relative performance.
In our example, since Product Pages underperforms, the base bid gets reduced to account for that. The other placements then increase from that reduced base bid based on how much better their conversion rates are.
(Pro tip: Check the placement mod column in the bid optimizer preview—it shows you how much base bids are being adjusted. A bid mod of 0.5 means a 50% reduction.)
You might notice recommended adjustments change even for well-performing placements. This is totally normal!
For instance, if Top of Search previously had a 129% adjustment and now shows 89%, that's a -40% delta. This doesn't mean performance dropped, it means:
The relative conversion rates between placements have shifted
The calculation uses updated historical data
The placement still warrants a significant increase (89%), it’s just recalibrated based on current performance
AdLabs optimizes placements by:
Focusing on relative conversion rates between placements
Setting the lowest-converting placement to 0%
Adjusting other placements based on how much better they convert
Controlling overall ACOS through keyword bid adjustments
Recalculating from scratch each time with fresh data
Remember:
ACOS alone doesn't indicate placement performance
Your target ACOS is separate from placement optimization
Lower ACOS doesn't automatically mean a placement is performing better
This approach helps you allocate ad spend more efficiently and improve overall campaign performance.
