We’ve tested Google AI Max over the past nine months, analyzing 23 individual tests across 16 already mature advertisers operating within a range of verticals. This article reveals what we did to maximize success with this campaign type.
Your experiments and observations may vary. If so, we’d welcome the debate.
This is intended to be just one voice among many in the conversation around AI Max. All the analyses we discuss are replicable within your own accounts, so you can ratify or dispute the findings based on your own data.
The ground rules for AI Max
Before launching an AI Max test, consider several factors. Two are particularly significant:
- Your campaigns should bid on a conversion action that’s meaningful for your business. Aim to get your conversion hygiene in as good a place as possible through tools like Enhanced Conversions and Google Tag Gateway. Value-based bidding is also ideal, although it’s not essential. Any automated targeting functionality can work.
- Your campaigns shouldn’t be budget-constrained. This advice is true in many situations, but it’s particularly relevant with AI Max. What’s the point of opening up your targeting if your budget prevents you from entering those auctions anyway? If your campaign is limited by budget, then either increase your daily budget headroom or set more conservative bid strategy targets.
With those prerequisites satisfied, we can now cover some of the juicier findings we’ve uncovered from our AI Max tests.
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Learning 1: Go all in with AI Max
AI Max performs best when you enable all three core features simultaneously:
- Search term matching.
- Text customization.
- URL optimization.
Overall, we saw a 40% higher uplift in test success rates for campaigns that used all three features compared to those that opted in only to the baseline search term matching functionality.
Text customization drives stronger performance
Google has been pushing the text customization concept in various guises for a few years. However, earlier versions, like auto-applied recommendations, have had limited uptake. So, we were keen to finally assess the impact this would have.
Using the Added by segment in the assets report, you can compare how text customization performs compared to standard advertiser-provided assets.
We found that AI-edited assets delivered an improved return on ad spend (ROAS) and helped extract more value per impression. Put simply, clients were better off when text customization was activated than when it wasn’t.
This trend was consistent across both headline and description assets, even though we found that text customization modified headlines far more often…
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