In the Facebook advertising system, as in other advertising platforms, there is machine learning. With machine learning, the optimization of the ads provided is more accurately ensured. After the ads are published, factors that change the efficiency of the ad, such as target audience, ad space, and broadcast time, are tested with each impression. The more ads are shown, the easier it is to optimize ad performance. However, as the name suggests, the ad performance may not be stable during the learning and trial process. CPAs are usually high. Advertisers may panic in this situation and make changes to ad sets, but this is a move that will negatively affect the learning process. We will discuss in detail which changes fundamentally affect the learning process in the later sections of our article.
Ad sets exit the learning stage when their performance becomes stable. Performance usually stabilizes after ad sets achieve about 50 optimization events within 7 days. Ad sets that fail to obtain sufficient optimization events or are expected not to obtain them become “Limited by Learning.” The Limited by Learning warning is an indicator that your budget is not being spent efficiently because the ad set cannot perform optimization. The main reasons for not being able to optimize are situations such as small target audience size, low budget, low bids, high auction overlap, or running too many ads simultaneously. To get your ads out of the Limited by Learning state, you can make the following adjustments:
In addition to these issues, there are other factors that prevent your ad sets from exiting the learning process. These factors are performed by advertisers. Some campaign, ad set, and ad edits reset the learning stage. Edits that cause the ad set to re-enter the learning stage:
In addition, when using Campaign Budget Optimization, changing your bid strategy can cause multiple ad sets within the campaign to re-enter the learning stage.
Some changes may not affect the learning process depending on the size of the change:
Also, adding new ad sets to your campaigns does not affect the learning process of your existing ad sets. In campaigns with multiple ad sets, changes you make in one ad set do not affect the learning process of your other ad sets.
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