Post by huangshi715 on Feb 15, 2024 1:49:11 GMT -8
Segment by target See how our test ads are doing great in our local campaigns but not so hot in our national campaigns? If you are going to aggregate stats to reach statistical significance more quickly, then you have to understand the performance differences in your targeting. If you don’t, you’ll choose winning ads that are actually losers in a different segment. Example 2: Mobile vs. desktop segmentationSimilarly, you shouldn’t aggregate stats together for mobile ads with desktop ads. Always handle mobile ads and desktop ads separately even if you only use a different display URL (such as m.domain.com/keyword).
You can see in the example below that our test ads are kicking butt on Switzerland Email List computers but are losing on mobile devices. mobile-vs-desktop-segment If we weren’t segmenting mobile and desktop, our results could be misleading. Example 3: Top vs. Other segmentationIn your AdWords account, the “Top vs. Other” segment shows you the difference in your data for ads that appear at the top of the search result page versus those that appear along the right hand column. Top vs other segment Well, you may have guessed it, but you shouldn’t lump stats for Top vs. Other together. Since Google uses the extended headline for “Top” ads, you will see a large .
Your “Top” ads are going to be your highest volume ads, so if you focus on optimizing the “Top” ads, you’re going to make the biggest impact with your ad copy testing process. Using wrong sample sizes There are so many articles about statistical significance in ad copy testing, yet plenty of people still stop running tests before they’ve had a chance to show meaningful results. Very often, this is because people get the sample size of their test wrong. There are many tools that exist to help determine the correct sample size for your ad copy tests: for starters, this tool predicts how many visitors you’ll need in order to have a conclusive A/B test.
You can see in the example below that our test ads are kicking butt on Switzerland Email List computers but are losing on mobile devices. mobile-vs-desktop-segment If we weren’t segmenting mobile and desktop, our results could be misleading. Example 3: Top vs. Other segmentationIn your AdWords account, the “Top vs. Other” segment shows you the difference in your data for ads that appear at the top of the search result page versus those that appear along the right hand column. Top vs other segment Well, you may have guessed it, but you shouldn’t lump stats for Top vs. Other together. Since Google uses the extended headline for “Top” ads, you will see a large .
Your “Top” ads are going to be your highest volume ads, so if you focus on optimizing the “Top” ads, you’re going to make the biggest impact with your ad copy testing process. Using wrong sample sizes There are so many articles about statistical significance in ad copy testing, yet plenty of people still stop running tests before they’ve had a chance to show meaningful results. Very often, this is because people get the sample size of their test wrong. There are many tools that exist to help determine the correct sample size for your ad copy tests: for starters, this tool predicts how many visitors you’ll need in order to have a conclusive A/B test.