Table of Contents
In Paid Search, you often face a frustrating dilemma: you want to scale a campaign, but the current keywords struggle to spend the daily budget in full, and the keyword research required to find new traffic for low-spend accounts rarely feels worth the time. You’re left with campaigns that underspend, underdeliver, and leave potential revenue on the table.
That’s exactly the challenge we set out to solve with a leading health supplements retailer when we ran an AI Max experiment in Google Ads. By toggling on this feature, we hoped to see whether AI Max could automatically expand our reach to new, relevant searches without requiring hours of keyword research and ad builds.
The results were mixed but left us optimistic: in just four weeks, our test campaign delivered 121% more impressions, 123% more clicks, and 160% more conversion value. But as with many experiments, the story isn’t just about the wins — it’s also about what the data revealed, and how those insights shape future testing.
The Challenge
This retailer had a search campaign that consistently struggled to scale. Despite strong products and a wide range of landing pages, the campaign rarely hit its daily budget, leaving opportunity on the table.
The issue was that we struggled to find keywords that resulted in search volume. Building out ad groups, keywords, and ads that resulted in relevant landing pages for searchers did not seem worth the time for an already low-volume campaign. The question became: could AI Max fill the gap by automatically identifying new, incremental searches and sending traffic to the right product pages?
If it worked, we’d save time while capturing growth that manual keyword builds might miss.
How We Scaled Performance with AI Max
Step 1: Select the Right Campaign
We chose a brand campaign that had consistently struggled to spend its daily budget in full. This gave us a strong testing ground — if AI Max could drive incremental scale here, the feature might prove valuable for other low-volume search campaigns.
Step 2: Set Up a Controlled Experiment
To ensure clean results, we created an A/B experiment in Google Ads with a 50% cookie-based traffic split between control and treatment arms. The control arm ran as usual, while the treatment arm had AI Max toggled on.
This setup gave us an apples-to-apples comparison to evaluate incrementality.
We allowed the test to run for four weeks without interruption. This gave AI Max enough time to gather signals and for us to observe meaningful performance differences across KPIs like spend, clicks, and revenue.
Step 3: Review Results and Search Terms
At the end of the test, the results spoke for themselves:
- Impressions: +121.6%
- Clicks: +122.7%
- Conversion Value: +160.3%
- Conversion Value / Cost: +18% (from 2.64 → 3.12)
While volume scaled significantly, efficiency didn’t increase at the same pace. Conversion value per cost improved by just 18%, which meant overall return remained below our target threshold.
Still, AI Max revealed a major advantage: incremental search coverage. Reviewing the search terms report, we found that the campaign began serving ads for previously untapped queries like “integrative therapeutics b12” and “integrative therapeutics theracurmin.” These were highly relevant terms that we weren’t targeting in the control campaign.
This showed that AI Max wasn’t just scaling volume — it was also uncovering valuable new search opportunities.
Results & Learnings
The experiment delivered clear takeaways:
- AI Max scales volume. Spend, clicks, and conversion value all increased by more than 120% compared to the control.
- Efficiency gains are modest. Conversion value per cost improved by just 18%, leaving overall efficiency below our preferred benchmark.
- Incremental searches matter. AI Max surfaced relevant queries we weren’t targeting, proving its potential to expand keyword coverage.
Ultimately, we chose not to roll out AI Max broadly for this retailer’s search campaigns — the return on spend wasn’t yet strong enough. However, the results were encouraging enough that we’re eager to test AI Max again with a brand that’s already at scale.
Conclusion
AI Max showed clear potential to drive scale and uncover new opportunities, but it wasn’t a perfect fit in this test. For advertisers with under-spending campaigns, it may be worth exploring as a way to capture incremental traffic without extensive keyword buildout.
The key takeaway: AI Max can expand reach, but advertisers should weigh efficiency carefully before adopting it at scale.
