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This can be done by setting up new campaigns and excluding locations in your ...

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发表于 2024-3-13 17:49:47 | 显示全部楼层 |阅读模式
Ads and Microsoft Ads. And depending on what platform you use there may be some testing tools available to help. There are no real wrong ways to test a hypothesis but there are some pros and cons you should be aware of with each of the following PPC testing examples. On/Off sequential testing This first testing example is likely the easiest for most advertisers. Here you take note of the data from your existing setup then make the changes that support your hypothesis run the campaign that way for a while then compare stats. Easy enough. ab testing examples  screenshot of sequential ab testing format It may look something like this.


You have four weeks worth of data with your evergreen ad copy. You then pause those variants IT Numbers and launch costfocused copy for four weeks then compare. This method of testing can be useful and can yield good results. Its easy to implement and only requires you to monitor your campaign for large swings in performance. The downside is that the variants never overlap with each other. Was there some seasonal effect that took place in the second weeks Were you short on budget for the month and needed to pull back on spending to hit your levels Did a news story impact performance for worse or better during either period Did any other aspects of the campaign change during the eight weeks the test was running Its not perfect but it can be useful to test sequentially to see results.







Geolocation testing In a geolocation testing example you keep the existing campaign set up as it is then create an experiment variant in a second location. This could be either to an expanded market or a portion of where youre currently targeting i.e. your campaign targets the entire United States but for this test you make the changes only effective in a handful of states. ab testing examples  geolocation targeting ab test example screenshot To accomplish this you need to make sure your control and experiment are mutually exclusive so theres no overlap.

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