If your Meta CBO campaign is overspending on one ad set while the others barely deliver, it’s usually caused by performance prediction, creative signals, audience overlap, or algorithmic pocket detection under Andromeda. This guide explains why Meta allocates spend unevenly - and how to regain control in 2025.

If you’re running a CBO campaign and see:
…you are experiencing Meta’s predictive spend allocation under the Andromeda system.
This behavior is common in 2025.
It doesn’t mean your campaign is broken.
It means the algorithm has made a decision - and it’s your job to understand why.
This article explains exactly why CBO overspends on one ad set, what it means, and the fixes that actually work.
CBO doesn’t aim for balance.
CBO aims for results.
Under Andromeda, Meta uses early behavioral signals to predict which ad set:
That ad set becomes the “primary route” — and gets most of the budget.
Let’s break down the real causes of uneven spend.
This is the single biggest reason.
Meta aggressively weights early performance indicators:
If one ad set gets even a slight early edge, Meta pours budget into it.
CBO magnifies small creative differences.
If multiple ad sets target overlapping populations, Meta:
This creates the illusion that “CBO chose a winner” when in reality:
your ad sets were competing with each other.
The more overlap, the stronger the imbalance.
Small audiences:
Meta deprioritizes them because they aren’t scalable.
Bigger audiences = more spend.
Andromeda is pocket-based:
Meta delivers ads into behavioral clusters of users with shared patterns.
If one ad set finds a “hot pocket,” Meta:
This can happen even if the audiences look identical.
Pocket discovery is normal and very powerful.
If one ad set has creatives that align better with:
Weak creative relevance = starvation.
Relevant creative → stronger predictive scoring → more spend.
CBO struggles when:
Meta funnels spend into the ad set most likely to gather optimization events quickly.
CBO prefers predictable conversion data.
Every CBO change forces recalibration:
Each change resets “confidence scoring.”
Until stability returns, Meta will only aggressively spend in one direction.
Editing is one of the most common causes of uneven spend.
Learning = low priority.
Optimized = high priority.
If 1 ad set exits learning, and 3 others are stuck in learning, CBO treats the optimized ad set as the only “safe” route.
Learning completion drives spend allocation.
This is your step-by-step method to rebalance delivery:
This is the fastest way to rebalance signals.
Fewer, larger surfaces → more stable allocation.
Do not touch it.
Do not throttle it.
Give it time.
Only kill an ad set if:
“Not spending” ≠ “bad.”
Ad sets perform better when creatives share:
Clustered signals improve allocation.
Then promote winners into CBO.
If the overspending ad set:
…then do nothing.
CBO is doing its job.
Uneven spend isn’t a glitch - it’s Meta’s prediction engine doing the heavy lifting.
Your role is to create an environment where multiple ad sets can perform well enough to earn spend.
Do that, and CBO becomes one of the most powerful scaling tools in 2025.