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Our guide to A-B testing your google ads

Let’s be honest, Google ads can be hard to get your head around sometimes. If you can’t dedicate time to learning the do’s and don’ts, then it’s natural to be unsure of what to do to help your campaigns.

Here at Populate, we have a great digital team, who absolutely love this sort of stuff and found this handy little guide on a best practices e-mail from Google, and thought we’d share!


Running experiments can help you understand the impact of your changes and improve campaign performance. To make it even easier for you to test in your account, the Experiments page can help you create, manage and optimise your experiments in one place.

So how do you go about it?


Set a clear hypothesis

Your hypothesis should reveal why you’re running the experiment and should be tied to your business goal.

Why: Your hypothesis will help you determine whether your experiment was successful or not.

For example, your hypothesis may be that switching your bidding strategy to Target

ROAS will drive a higher conversion value for your acquisition campaigns compared to Target CPA.


Create your experiment

Test one variable at a time.

Why: Testing more than one variable at a time makes it difficult to identify which element drove the better outcome.

For example, you might be trying to compare two different headlines

for your responsive search ad, but if you also use two different bidding strategies, you won’t know whether it was the headline or the bidding strategy that contributed to the winning experiment.


Pick one or two metrics to gauge the success of your tests before a test begins.

Why: This will most often be the main goal for your account, such as total sales or cost per action. When it’s time to end a test, let that metric tell you the winner.


Avoid making changes to your base campaigns unless sync is on.

Why: When you make changes to a base campaign during an experiment, it becomes difficult to understand which of those changes impacted your original experiment.


Analyse results and choose experiment winners

Implement what you’ve learned in your future campaigns.

Why: The most critical step of any experiment is updating your tactics based on what you’ve learned. You have the option to update an original campaign or convert to a new campaign. Updating an original campaign will port all changes over to your current campaign, which preserves that campaign’s history. Consider new campaigns if you’re testing a new campaign structure, or if you want to preserve findings from a learning period, update your original campaign.


Keep records of your experiments.

Why: As you continue testing in your account, prioritising what to test will be easier if you keep records of tests you’ve performed in the past. Plus, standardising insights from past experiments will help you tap into them for your next campaign, and track and benchmark the value of your efforts.

So there you have it.

A quick guide on how to A-B test effectively. If you have any questions, feel free to reach out and we’d be more than happy to help.

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