advertising effectiveness

Tino Meta said:
With the same campaign structure, ad content, and target audience, why can the results differ significantly between advertising accounts? Do you know what factors might be causing this difference?
Click to expand...
Even with identical content, every time you launch a campaign on a new account, machine learning restarts.
In the first 50 results, Facebook will test distribution to different segments of your customer base.
Account A might be lucky enough to reach easy-going people and close deals right away, allowing machine learning to optimize accordingly. Account B might fall into the group of people who only view without buying, causing the algorithm to be misled from the start.
Furthermore, even a few minutes' difference can result in different competitors in that auction.
that's why
 
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From what I've observed, Facebook still treats different accounts differently based on their history. Long-standing, stable accounts with consistent spending are prioritized for better ad visibility, while new or high-risk accounts have limited visibility and higher CPMs.
 
Different ad accounts can perform differently due to account trust history spending behavior learning phase data and internal quality scores
 
Tino Meta said:
With the same campaign structure, ad content, and target audience, why can the results differ significantly between advertising accounts? Do you know what factors might be causing this difference?
Click to expand...
The main difference lies in account reliability and initial signal quality, not the structure; a stable account with good early engagement will always yield vastly different results even with the same setup.
 
Results can differ because each ad account has different history, trust signals, and learning data. Auction timing, competition, and early engagement signals also affect delivery, even with identical setups.
 
Even with identical setups, ad performance can vary because each account has its own history and signals. Differences in account age, trust level, past results, learning data, payment behavior, and tracking quality all influence delivery. The platform also evaluates and distributes ads differently across accounts, so some variation in results is completely normal.
 
The same question and the same campaign, when duplicated into multiple smaller versions on the same account, will result in different academic reach rates for each campaign, leading to different results, and the same applies to accounts.
 
It’s normal for ads to perform differently across accounts, as each one is evaluated based on its own history, transparency, and trust signals. I’m also running tests on multiple accounts to compare performance and see which setup works best.
 
Even with the same set of ads, the results can be different because Facebook evaluates not only the content, but the entire process, and is influenced by the account, Business Manager, page, payment method, and how the ads are run.
 
Meta doesn't evaluate ads independently, but always considers them in the context of the account's history and trustworthiness.
Therefore, even with the same campaign structure, ad content, and target audience, results can still differ significantly due to differences in activity history, spending behavior, payment quality, site reputation, and the overall trustworthiness the system assigns to each account. These factors directly impact delivery, CPM, and auction effectiveness.
 
Because when identical campaigns are launched, the ads reach different audience segments. The account history, allocated budget, number of leads, and results also have a significant impact, but most often, the ads simply reach different audiences, regardless of the identical settings.
 
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