Google Ads Campaign Mix Experiments In Beta

Jan 26, 2026 - 7:21 am 0 by
Filed Under Google Ads

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Google Ads has a new help document named Campaign Mix Experiments (Beta). This describes how advertisers can test multiple campaign types, budgets, and settings across campaigns in a single experiment.

Google said advertisers "can run an experiment across your campaigns using various campaign types, and identify the most effective strategies for your business goals."

Dario Zannoni posted about this on LinkedIn and wrote, "Google is expanding its lineup of ad experiments, and this new type looks very very promising. Campaign Mix Experiments makes it possible to test different campaign setups, even combining multiple campaigns of different types."

Campaign Mix Experiments allows you to select existing campaigns and assign them to different experiment arms (up to 5 total). This approach offers flexibility in testing various scenarios, including:

  • Account structure testing: Evaluate which campaign combinations are ideal for your business objectives.
  • Campaign consolidation: Test the impact of consolidating multiple campaigns into a single campaign.
  • Cross-campaign budget optimization: Assess different ways to optimally allocate your budget across campaign types to identify the most efficient strategy.
  • Feature adoption: Compare the performance of different features or settings across campaigns.
    • Note: For testing specific individual features, like Broad Match, Google recommends using the dedicated feature experiment, for example, Broad Match Experiments, instead of Campaign Mix Experiments.

You can review the reporting metrics on the “Experiment summary” page. From there, you can view how your arms are performing across metrics like Cost / Conv., Avg. CPM, and Conv. rate, along with details about how the arms are performing compared to each other.

"While the minimum duration can vary depending on the experiment type and settings, aim to run your experiment for at least 6 to 8 weeks to collect enough data for reliable results," Google wrote.

Forum discussion at LinkedIn.

 

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