AI Max in action: What early case studies and a new analysis script reveal

Google’s AI Max for Search campaigns is changing how we run search ads. 

Launched in private beta as Search Max, the feature began rolling out globally in late May, with full availability expected by early Q3 2025. 

But will AI Max actually drive incremental growth or simply take credit for conversions your existing setup would have captured anyway? 

This article:

• Breaks down the key metrics to track in AI Max.
• Shares early results from travel, fashion, and B2B accounts.
• Includes a Google Ads script to make analysis faster and easier.

Understanding AI Max

Think of AI Max as Google combining the best parts of Dynamic Search Ads and Performance Max into regular search campaigns. 

It does not replace your keywords. Instead, it works alongside them to find more people who want what you’re selling.

AI Max does three main things.

• Finding new search terms your keywords might miss, using search term matching.
• Writing new ad headlines and descriptions that match what people are actually searching for.
• Sending people to the best page on your website instead of just the one you picked.

The real game changer came in July 2025, when Google began showing AI Max as its own match type in reports. 

Before this, figuring out what AI Max was doing felt like looking into a black box. 

Now, we can finally see the data and make smarter decisions.

Evaluating AI Max: Metrics that matter

When you’re looking at AI Max performance, start with the basics. 

Open your search term tab and look for the Search terms and landing pages from AI Max option. 

This lets you see AI Max results separately from your exact match, phrase match, and broad match keywords.

Compare conversion share and budget share

The first thing to check is how many conversions come from AI Max versus your regular keywords. 

If AI Max is bringing in 30% of your conversions but eating up 60% of your budget, you know something needs attention. 

Look at the cost per conversion, too. 

AI Max might cost more at first, but that’s normal while Google learns what works for your business.

Look beyond cost – focus on conversion rates

Don’t just focus on the cost. Pay attention to conversion rates. 

AI Max often finds people who are ready to buy but use different words than you expected. These new search terms can be gold mines if you spot the patterns.

One of AI Max’s biggest benefits is finding search terms you never thought to target. 

Look at your search terms report and filter for AI Max queries. You’ll probably see some surprises.

Let’s say you sell running shoes and target “best running shoes.” AI Max might show your ads for “comfortable jogging sneakers” or “shoes for morning runs.” 

These are people who want the same thing but use different words. The smart move is to add these high-performing terms to your regular keyword lists.

Identify irrelevant traffic 

If you’re getting clicks from people searching for “cheap shoes” when you sell premium products, add “cheap” as a negative keyword. 

AI Max respects negative keywords, so use them to guide the system toward higher-quality queries.

Dig deeper: Google’s AI Max for Search: What 30 days of testing reveal

Tracking the learning process

Every AI system needs time to learn, and AI Max is no different. 

Plan for a learning phase

The first few weeks often look expensive because Google is still figuring out what works. Don’t panic if your costs jump initially.

Track your performance daily during the first month

As AI Max learns your patterns, you should see costs stabilize and conversion rates improve. If things keep getting worse after three weeks, then it’s time to make changes.

Keep an eye on the types of search terms AI Max finds over time

Early on, you might see lots of random queries. As the system learns, the terms should become more relevant to your business goals.

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When things go wrong

The biggest mistake people make is changing too much, too fast. 

AI Max needs data to work properly, and constantly adjusting things prevents the system from learning.

That said, some problems need quick fixes. 

• If AI Max is spending money on completely irrelevant searches, add negative keywords immediately. 
• If the AI creates ads that violate your brand guidelines, remove those assets right away.

Watch your overall account performance, not just AI Max numbers. 

Sometimes, AI Max might look expensive on its own, but it actually helps your other campaigns perform better by capturing different types of traffic.

Planning for the future

AI Max is still evolving, and Google keeps adding new features. 

To adapt:

• Build reporting systems that can grow with these changes. 
• Set up automated reports for the metrics that matter most to your business.
• Don’t try to control everything. 

The businesses seeing the best results from AI Max are the ones that:

• Set clear goals.
• Provide good data.
• Let the system do its job. 

Your role shifts from managing keywords to managing strategy.

Start testing AI Max on a small scale if you’re nervous about it. For example:

• Create one campaign with AI Max enabled and compare it to your existing campaigns.
• Run an AI Max for Search campaign experiment and let Google evaluate if the experiment is statistically valid. 

Once you see how it works for your specific business, you can decide whether to expand.

Case studies: AI Max in action

These are early results from a limited data set and shouldn’t be viewed as statistically significant. 

I’m sharing them to illustrate what I’ve seen so far – but the sample size is small and the timeframe short. Take these numbers with caution.

Case 1: Tourism and travel

This advertiser already had a solid search setup and was seeing good results. 

Growth, however, was difficult because of heavy competition and the fact that strong keywords were already in play within a modern search structure.

Match type	Avg. CPC (€)	CVR (%)
AI Max	€0.11	1.47%
Broad match	€0.09	3.79%
Exact match	€0.53	9.00%
Exact match (close variant)	€0.22	7.11%
Phrase match	€0.16	6.25%
Phrase match (close variant)	€0.11	3.27%

AI Max generated additional conversions, but relative to the existing setup the impact was limited. 

The conversion rate was much lower than other match types. 

Because the average CPC was low, there was no cost spike, but performance still lagged.

Broad match – also known for surfacing broader, newer queries – had an even lower CPC (€0.09) and a conversion rate more than twice that of AI Max. 

In this account, AI Max’s contribution was minor.

Search term overlap analysis showed AI Max had a 22.5% overlap rate, meaning 77.5% of queries were new to the campaign. 

That’s a fairly good sign in terms of query discovery.

Case 2: Fashion ecommerce

This account focused on women’s clothing and already had a well-optimized campaign. 

The goal was to expand reach during the competitive holiday season, when exact match keywords became increasingly expensive.

Match type	Avg. CPC (€)	CVR (%)
AI Max	€0.08	2.15%
Broad match	€0.12	2.89%
Exact match	€0.67	8.45%
Exact match (close variant)	€0.28	6.78%
Phrase match	€0.19	5.92%
Phrase match (close variant)	€0.14	4.11%

AI Max performed well here, delivering the lowest CPC at €0.08 and a respectable 2.15% conversion rate. 

Although conversion rates were lower than exact and phrase match, the cheaper clicks kept cost per acquisition competitive. 

AI Max also captured fashion-related long-tail searches and seasonal queries that the existing keyword set had missed.

Notably, AI Max outperformed broad match with both lower costs and better conversion rates. 

This suggests its ability to better understand product context and user intent – especially important in fashion, where search terminology is diverse.

Search term overlap analysis showed only an 18.7% overlap rate, meaning 81.3% of queries were completely new. 

That level of query discovery was valuable for extending reach in a highly competitive market.

Case 3: B2B SaaS

This account promoted project management software and had a mature strategy focused on high-intent keywords. 

Conversion tracking was strong, measuring both MQLs and SQLs. 

The client wanted to test AI Max for additional lead generation opportunities.

Match type	Avg. CPC (€)	CVR (%)
AI Max	€0.89	0.76%
Broad match	€0.72	1.23%
Exact match	€1.84	4.67%
Exact match (close variant)	€1.22	3.91%
Phrase match	€1.05	3.44%
Phrase match (close variant)	€0.94	2.88%

In this case, AI Max struggled. Despite a reasonable CPC of €0.89, the conversion rate was just 0.76%. 

That pushed CPA well above the client’s target, making AI Max the worst-performing match type in the account. 

It tended to capture too many informational searches from users not yet ready to convert.

Even broad match, typically associated with lower-intent traffic, outperformed AI Max with a 1.23% conversion rate at a lower CPC. 

The complexity of the B2B buying cycle favored exact and phrase match keywords over AI Max’s broader interpretation.

Search term overlap analysis showed a 31.4% overlap rate, leaving 68.6% of queries as new. 

However, these were mostly low-intent informational searches that didn’t align with SQL goals – underscoring the importance of high-quality conversion tracking when evaluating AI Max.

Wider industry sentiment

Advertiser feedback so far mirrors these mixed results. 

In a recent poll by Adriaan Dekker, more than 50% of respondents reported neutral outcomes from AI Max, while 16% saw good results and 28% reported poor performance.

Tips to analyze AI Max search terms

You can analyze AI Max queries in Google Sheets using a few simple formulas. If your search term report has the term in column A and match type in column B:

• To check whether a search term appears in both AI Max and another match type:

=IF(AND(COUNTIFS($A:$A;A2;$B:$B;"AI Max")>0;COUNTIFS($A:$A;A2;$B:$B;"<>AI Max")>0);"Overlap";"No Overlap")

• To count how many match types trigger a given term:

=COUNTIFS($A:$A;A2) can be used to count how many match types trigger on that search term.

• To measure query length with an n-gram analysis:

=(LEN(A1)-LEN(SUBSTITUTE(A1," ","")))+1

These checks show whether AI Max is surfacing unique queries, overlapping with existing match types, or favoring short-tail vs. long-tail terms.

Because AI Max is still in early stages, it’s hard to draw firm conclusions. 

Performance may improve as the system learns from more data, or remain flat if your setup already covers most transactional queries. 

That’s the question advertisers will answer in the coming months as more tests and learnings emerge.

So far, results can be positive, neutral, or negative. 

In my experience, neutral to negative outcomes are more common – especially in accounts with strong existing setups, where AI Max has fewer opportunities to add value.

A Google Ads script to uncover AI Max insights

To make analyzing AI Max performance easier, I created a Google Ads script that automatically pulls data into Google Sheets for deeper analysis. 

It saves hours of manual work and includes the exact formulas mentioned earlier in this article, so you can immediately spot overlap rates and query patterns without manual setup.

The script creates two tabs in your Sheet:

• AI Max: Performance Max search term data with headlines, landing pages, and performance metrics.
• Search term analysis: A full comparison of all match types, including AI Max, with automated formulas.

The analysis covers:

• Overlap detection between AI Max and other match types.
• Query length analysis (short-tail vs. long-tail).
• Match type frequency counts to identify competitive terms.
• Automatic cost conversion from Google’s micro format into readable currency.

How to use it:

• Create a new Google Sheet and copy the URL.
• In Google Ads, go to Tools > Scripts.
• Paste the script code and update the SHEET_URL variable.
• Run the script to automatically populate your analysis.

With this setup, you can quickly calculate the same metrics I used in the case studies – like the 22.5% overlap rate in the tourism account or the 81.3% new query discovery in fashion. 

The automated workflow makes it easier to see whether AI Max is surfacing genuine new opportunities or simply redistributing existing traffic.

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