Experiments with ads
Why experiment with ads?
For each ad in Yandex Direct, you can prepare multiple promotional materials, and the ones with the highest CTR will be shown to your audience automatically. This will help you understand which ad materials are better at attracting your target audience and thus ensure that your placement gets you better results.
Such experiments are called A/B experiments or split testing.
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A/B testing is one of the easiest and most widely used methods in marketing research. With this approach, users are shown different versions of an ad or site element under the same conditions. e.g., of a title or ad text. Statistics show which of the versions is preferable to the target users. |
Options to start testing
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First, categorize your keywords by types of your products/services. For example, if you sell bicycles, you can categorize your keywords in the following way: mountain bikes, city bikes, kids’ bikes and bmх.
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Then prepare several ad texts that you would like to test for each group of keywords.
You may test a wide range of variants, e.g., talk about a discount, highlighting that this is a limited-time offer.
Or specify the models you wish to include in the offer.
Try experimenting with images as well as texts.
and sitelinks.
This way, you can run A/B tests for almost any element of your ad in Yandex Direct.
Alert
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Make sure that every version of your promotional content in the ad group matches the keywords.
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We recommend testing versions for one ad element at a time. For example, test only different texts or different images. If all the ad elements are different, this will make it difficult to assess each element's contribution to the overall performance.
Experiment procedure
At the first stage , all the ads in the group will be displayed in the rotation. As soon as enough statistics is accumulated, the system will automatically identify and display the most clickable ad for each keyword more often. You can disable or edit ads that are less effective at any time.
Here is an example of a change in the CTR and ad impression share for two ads in a group that were served in premium placement positions over a calendar month. The diagrams show that the more clickable ad is gradually displayed more often, contributing to the growth of the total group CTR.
This example illustrates the principle by which an ad group functions. However, the experiment may develop in other ways as well. Every case is special and the results of each testing are affected by a number of factors.
Note
Many factors (user behavior, the season, hour of the day, etc.) are taken into account to identify an ad with the best CTR. That is why the number of impressions of each ad in a group varies.
Have questions?
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