The AB Testing for Ads optimization is a data-driven tool that helps you compare ads with statistically significant data in the same ad group. It helps you find ads that meet your business goals or contribute to the success of your advertising campaign and remove those that are not performing well with a single click.
The system analyzes and tabulates the ads for comparison under each ad group, filtering only the underperforming ads based on the selected criteria. The analysis takes into consideration data pulled in real time from your AdWords and Bing Ads account, and it can look up to 180 days of data.
The optimization makes the recommendations based on one of three parameters (CTR, Conversion Rate and Conversion per Impression) and considers only ads with statistically significant data.
The optimization identifies the best and worst performing ads in active ad groups (including image ads for display and expanded text ads for search), allowing the analysis of the suggestions by comparing clicks and conversions parameters side by side before pausing the lowest performance ads.
The system also recommends high performing headlines, description lines and display URLs (from your best performing ads) to create new ads in the ad groups where you are pausing ads with a lower performance.
You can access the A/B Testing for Ads in the Optimizations tab, and under "For Ads".
Select the campaigns or labels for which you want to see results. You can also see any labels that have been assigned to the ads in AdWords. These can some in handy if you've labeled winning ads and ads that are currently in testing in AdWords
Select the date range you want to take into consideration for the statistical analysis. By default, the system looks at last 30 days.
Search, Display or both.
The AB Testing for Ads optimization identifies winning and losing ads in each ad group, but it requires data to be statistically significant before making a recommendation. However, there are times when an account doesn’t have enough traffic to make a decision based on statistical significance, or you want to optimize your ads early on.
To be able to use the optimization in those cases, we launched the Turbo Mode. When you turn on the Turbo Mode in AB Testing, you'll see all active ad groups with all active ads in them.
These settings let you select the parameters you are going to use to find the ads.
Test Required Confidence:
This setting lets you choose the confidence level you need the system to be (mathematical accuracy) for the results. You can select one of the three available settings (90%, 95%, and 99%). For example, when you choose 99% it means that the system is 99% sure of the results it shows. Usually, as the confidence percentage increases, the number of suggestions decreases. We recommend using a 95% confidence setting in most cases.
Yes (only compare mobile preferred ads), no (don't include mobile preferred ads in the comparison) or both (include both mobile preferred and desktop ads).
Consider Ads with Impression count at least:
You can choose between 100, 500 and 1000 impressions.
Number of ad groups to test:
The maximum number of ad groups shown at a given time.
Ad Type to Test:
You can choose to see results for text, image and dynamic ads. For text ads, you can chose to compare legacy text ads and expanded text ads with their own kind and against one another. When you select "image", ads make sure to change the network to display to see results.
Find winner by:
You can choose between CTR, Conversion Rate, and Conversion/Impression (Combination of CTR and Conversion Rate). We recommend using CTR because the purpose of the ad is to get the user to click and go to the site
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