I duplicated a successful ad group.

New ad groups don’t inherit data and must relearn from scratch. The original ad group has historical advantage and is prioritized. Identical ad groups also compete internally, so only one tends to win.
Try scaling the original ad group, or duplicate it while changing one variable (budget or audience).
 
Probably the Facebook algorithm is in the learning phase. Or the old ad set is performing well, so Facebook is focusing delivery on it.
 
Reusing the old structure only creates audience cross-referencing, generating automated ad groups that combine to provide internal pricing. Instead, we need to focus on building campaign translations to deliver real 'prices' for the color team. Only by directly setting things up from scratch can staff understand the operational logic and master the skills to handle fluctuating environments, rather than just adjusting based on pre-existing templates.
 
You can wait 3-5 hours for the copy campaign to show results; in reality, the copy cannot be exactly the same as the original, that's due to Meta's algorithm.
 
identical structure doesn't mean identical treatment in delivery. the original ad group benefits from its historical data, auction momentum, already-optimized audience pockets, and duplicates are re-entered into exploration. until they accumulate enough events, it's normal for results to be unstable or not deliver at all
 
That's right, by copying the same campaign, Facebook can allocate ads to different items and distribute the results evenly, rather than increasing the budget to achieve better results.
 
Sometimes, a copied campaign can yield better results, and vice versa; this depends on whether each campaign's academic approach is sufficiently comprehensive.
 
Meta’s algorithm will always favor ad sets that already have strong historical performance.
Also, when you duplicate them, you’re basically making your campaigns compete against each other, Meta will push more budget toward whichever ad set is currently winning.
 
As I suspected, I should wait a little longer and observe these ad groups. I anticipate that they will definitely yield results because there is a potential audience of buyers among them.
What's the update? Do you see results now?
 
Meta’s algorithm will always favor ad sets that already have strong historical performance.
Also, when you duplicate them, you’re basically making your campaigns compete against each other, Meta will push more budget toward whichever ad set is currently winning.
My idea is that having multiple ad groups targeting the same interest keyword will reach more potential customers.
 
What's the update? Do you see results now?
It's very disappointing. The number of people adding items to their shopping carts is increasing, but it's not translating into results. The same ad creative is still only generating results in the original ad group.
 
Sometimes, a copied campaign can yield better results, and vice versa; this depends on whether each campaign's academic approach is sufficiently comprehensive.
Copying the winning ad group's strategy is the right approach, because the number of people interested in each keyword is enormous, and a single ad group cannot completely cover the entire audience, making the learning process very long.
 
New ad groups don’t inherit data and must relearn from scratch. The original ad group has historical advantage and is prioritized. Identical ad groups also compete internally, so only one tends to win.
Try scaling the original ad group, or duplicate it while changing one variable (budget or audience).
Your suggestion is crucial; it's true that multiple identical ad groups without changing any variables will lead to unhealthy competition and abnormal spending, which is a very bad thing.
 
Meta algorithm still counts your ad group as the old one, and they won't pour it cause the audience file is limited. You can copy the ad group, but you should change the ad creative and content
 
Yes, this is normal and usually related to the learning phase and delivery reset. Duplicated ad groups start with no historical data, so performance can differ even with identical settings, while the original benefits from accumulated optimization signals.
 
New ad sets don’t carry over historical data, so they need time to relearn from the beginning. The original ad set usually has an advantage because of its past performance and optimization history. When multiple identical ad sets run at the same time, they can also compete with each other, and typically only one performs well.
A better approach is to scale the original ad set, or duplicate it while adjusting just one factor, such as the budget or the audience, to avoid internal competition.
 
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