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Lets say were trying to improve the CPA for an account. Here are some ways I could phrase my success metric: Target performance: This test is a success if the experiment variable yields a $ CPA. Percentage improvement: This test is a success if the experiment variable has a lower CPA than the control. Statistical significance: This test is a success if the experiment variable has an confidence level of performing better than the control. All of these are valid ways of measurement.
Choose the one that works best for your purposes. Are your key PPC metrics up to industry standards Find out with our latest search ad benchmarks and new Facebook ads benchmarks! Set PPC testing limitations and dealbreakers Iceland Phone Number Now lets get into some of those other metrics I alluded to. , that doesnt mean that all other metrics are going to stay flat. In fact, Id venture to bet that many of them will change quite a bit. Its up to you to decide what is an acceptable level of change on other stats. Maybe you dont care if your click-through rate goes down as long as cost per lead goes down to a profitable level. Maybe you dont mind if you see a cost per click increase as long as revenue stays stable. But not everyone is alright with other stats moving too much.

Heres an testing example including varying metrics: I have a client who wanted to decrease the cost per lead on his branded terms by , but he wasnt willing to let impression share dip below . While we knew it was going to be tricky to thread the needle, we set up an testing experiment for target CPA bidding to try and lower the CPA. As we got into it, we realized that to hit our CPA metric, Google only showed the ads for about of the impressions we could have had. That was a dealbreaker for him, so we turned the test off and found another way. ab testing examples - google ads experiment goals screenshot When you set up experiments in Google, they even ask for two key metrics and what you plan to
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