Google Claims AI Overviews Monetize At Same Rate As Traditional Search via @sejournal, @MattGSouthern

Google claims that search results with AI Overviews generate the same amount of advertising revenue as traditional search results.

This claim was made during Google Marketing Live when the company revealed plans to expand AI Overview ads to desktop users and more English-speaking markets.

If true, this could reshape how marketers perceive Google’s AI-powered future. However, the claim raises questions about how Google measures success and what it means for your campaigns.

Marketers need to understand what lies behind these claims and what they indicate for the future of search advertising.

AI Overviews Reaches Massive Scale

Google launched AI Overviews on mobile in the US last year. Since then, the company has quickly expanded the feature worldwide. It now processes AI-generated responses for users in more than 200 countries.

Shashi Thakur, Google’s VP/GM of Advertising, stated during the press session:

“We started rolling out AI overviews in search on US mobile last year. At this point, we are reaching a billion and a half users using it every month.”

Thakur oversees advertising across Google’s search products. This includes Google.com, Discover, Image Search, Lens, and Maps. He noted that users are happy with the feature.

The expansion shows Google’s confidence in both user adoption and commercial success. The company announced the desktop expansion that morning at the event, representing the latest phase of their rapid global rollout.

Thakur explained the growth impact:

“The consequence of us building AI overviews is that people are seeing growth. People are asking more of those questions… So we are seeing growth. So people are asking more questions. Many of those questions are even commercial. So we are seeing a growth even in commercial.”

Google’s Broader Vision For Search Evolution

Google’s approach to AI Overviews reflects a fundamental shift in how the company thinks about search capabilities. Thakur outlined this vision:

“At its core, we think about search as expanding the kinds of curiosities you can express. Humans have innumerable number of curiosities. There’s only a fraction of those that gets expressed to search. The more we advance the technology, the more we advance the product, users can bring more of their curiosities to search.”

This philosophy drives Google’s push toward AI-powered responses that can handle more complex and nuanced queries than traditional keyword-based searches.

How Google Measures AI Overview Monetization

Google’s revenue claims are based on controlled experiments. The company compares identical search queries with and without AI Overviews. They use standard A/B testing methods.

This means showing the AI feature to some users while holding it back from others. Then they measure the revenue difference.

Thakur explained to reporters:

“When we say AI overviews monetizes at the same rate, if you had taken the exact same set of queries and not shown AI overviews, it would have monetized at some rate. This continues to monetize at the same rate.”

The testing focuses on overall business value and revenue. It doesn’t examine individual metrics, such as click-through rates. Google emphasized this represents performance across many queries, not individual searches.

For advertisers, this suggests AI Overviews don’t hurt existing search advertising effectiveness. However, the long-term effects of changing user behavior patterns remain unclear.

Shashi Thakur speaks to press at Google Marketing Live.
Photo: Matt G. Southern/Search Engine Journal.

Strategic Approach To AI Overview Advertising

Google states that ads within AI Overviews adhere to the same quality guidelines as traditional search ads. The company requires that ads be of high quality and fit well with the user experience. All ads must be marked as sponsored content.

Advertisers have three placement options for AI Overview ads: above the AI response, below the response, or integrated within the AI answer itself. This gives marketers flexibility in how they appear alongside AI-generated content.

The complexity of modern user behavior drives Google’s advertising strategy. Thakur noted:

“I think the main thing to take away from those conversations is user journeys are complicated. And users get inspiration to get into their commercial journeys at innumerable points in their journeys.”

The integration focuses on identifying commercial intent within complex queries through what Google refers to as “faceted” searches. These are complex questions that contain multiple sub-questions, some of which have commercial intent.

Thakur gave an example of a user asking about airline rules for traveling with pets. That person might then need pet carriers or travel accessories, creating natural opportunities for advertising. The AI system can identify these layered commercial needs within a single complex query.

Google uses various classifiers to identify commercial intent, including shopping queries, travel queries, and insurance queries. This automated classification system helps match ads to relevant user needs.

Thakur stated:

“Ads need to be high quality, and they need to be cohesive with the experience. Ads of this nature extend how good the answer is for certain users.”

Google reports positive user feedback about ads shown with AI Overviews. This suggests the integration doesn’t significantly hurt user satisfaction.

This user acceptance seems crucial to Google’s strategy. The company plans to expand AI Overview advertising to more platforms and markets.

Shashi Thakur speaks to press at Google Marketing Live. Photo: Matt G. Southern/Search Engine Journal.

Implications For Digital Marketers

The revenue parity claim addresses advertiser concerns about AI’s impact on search advertising effectiveness.

Thakur acknowledged the fundamental question marketers are asking:

“So now, the question we often get from our advertisers, and it’s a natural question, which is, this is great. Search is evolving in lots of exciting directions. How do we participate? And how do we connect with our customers in the context of this evolving experience?”

Thakur noted that over 80% of Google advertisers already use some form of AI-driven advertising technology. This suggests the industry is ready for more AI integration.

However, the shift toward AI-powered search responses may require advertisers to adapt their strategies. Users are asking increasingly complex, longer queries. Traditional keyword targeting may not be effective in addressing these.

Google’s solution involves increased automation through tools like the newly announced “AI Max for search” feature. Early beta testing of AI Max has shown promising results, with advertisers experiencing an average 27% increase in conversions while maintaining similar return on investment (ROI) targets.

Thakur explained the motivation behind AI Max:

“So the motivation for this, essentially, was this changing user behavior. That’s number one. As we heard from our advertisers, we got the feedback very clearly that transparency and control of the form, they were already used on search campaigns. That continues to be super important in addition to the automation.”

The tool maintains the transparency and control features that advertisers expect from traditional search campaigns, including keyword performance reporting and campaign controls. This addresses concerns about losing visibility when embracing automation.

The company’s emphasis on automation reflects a challenge. It’s hard to match ads to sophisticated, conversational queries that can contain multiple commercial intents.

Manual keyword strategies may become less effective over time. This is especially true as search behavior evolves toward natural language interactions.

AI Mode Expansion Creates New Opportunities

Beyond AI Overviews, Google is testing ads within its new AI Mode, which enables fully conversational search experiences. Early data indicates that users in AI mode ask questions that are up to twice as long as regular search queries.

These longer, more conversational queries create additional opportunities for identifying commercial intent within complex questions. The extended query length often means users are providing more context about their needs, potentially making ad targeting more precise.

Google is applying lessons learned from AI Overviews to ensure ads in AI mode maintain the same quality and user experience standards.

Looking Ahead

Thakur emphasized that Google’s approach remains focused on delivering a high-quality user experience while providing business value to advertisers.

The actual test of Google’s revenue claims will come as AI Overviews mature. User behavior patterns need time to solidify.

As Google continues expanding AI Overview advertising globally, digital marketers face a balancing act. They must embrace new automated tools while maintaining the control and transparency that drive successful campaign performance.

Featured Image: Mijansk786/Shutterstock

Google Announces Largest Ads Bidding Update In Over A Decade via @sejournal, @brookeosmundson

PPC bidding just got a lot more interesting.

Just announced at Google Marketing Live, Google is launching Smart Bidding Exploration, a new opt-in feature designed to help advertisers capture more conversions from their existing campaigns.

This update marks one of the most significant changes to Google Ads bidding over a decade.

This isn’t a cosmetic update or a tweak to an existing bidding model.

It’s a fundamental shift in how Google allows advertisers to find value in queries they’ve likely been overlooking.

If you’re focused on maximizing ROAS or sticking tightly to past performance data, this is one update worth paying attention to.

How Does Smart Bidding Exploration Work?

Smart Bidding Exploration works within the bounds of your existing campaign structure.

It doesn’t expand your audience targeting or broaden your keyword strategy (no pun intended).

Instead, it allows the bidding algorithm to more aggressively pursue opportunities you were eligible for, particularly on Broad match and Dynamic Search Ads (DSA) campaigns.

But, there is a catch for using it: you’ll need to allow some flexibility in your ROAS targets to use it.

Advertisers can opt into Smart Bidding Exploration by giving Google permission to bid below their typical ROAS threshold, generally in the 10-30% range.

That means Google may raise your bids on certain queries if its AI systems determine those queries could convert at a healthy volume and cost.

Smart Bidding Exploration is a different approach to just adjusting ROAS targets across the board at the campaign level. In fact, constantly adjusting ROAS targets could cause more volatility in performance instead of improving it.

Instead, Smart Bidding Exploration fine-tunes bidding for queries that would otherwise be filtered out.

What You Can Expect From Reporting

While advertisers won’t see a detailed breakout of every new search query due to privacy threshold, Google is giving visibility into the impact of Smart Bidding Exploration through the Bid Strategy report.

You’ll be able to track:

• The number of unique search categories generating impressions and conversions
• How much traffic came from these categories
• The volume of new conversions compared to your baseline

While the reporting is currently aggregate, Google is looking for more granular visibility on the roadmap.

The feature is also compatible with Drafts & Experiments, so you can run clean A/B tests to isolate results.

Support for Portfolio Bid Strategies is included at launch, and SA360 support is expected soon.

Why Should Advertisers Test This?

For marketers managing Search campaigns that have stalled in growth or seem overly narrow in scope, this could be a solid way to unlock additional conversions.

The feature offers a way to capture more conversions without blowing up campaign structure or budget.

Additionally, this feature is not changing your audience targeting. That’s an important distinction.

For example, Optimized Targeting on Display or Demand Gen actively expands who sees your ads.

Smart Bidding Exploration doesn’t do that. It keeps your targeting exactly as is, but unlocks the potential to show up for queries you wouldn’t have previously been eligible to show for, all within your existing targeting.

If you’re running campaigns that are too tightly bound by a strict ROAS target, you may be unintentionally capping performance.

Smart Bidding Exploration is a way to loosen those constraints just enough to let Google’s AI find opportunities you didn’t realize were there.

What This Signals From Google

Smart Bidding Exploration is more than just a new feature toggle.

It’s a fundamental shift in how we think about conversion opportunity within Google Ads.

Marketers are often pushed to optimize for what they already know works, especially under pressure to hit ROAS or CPA goals. But that approach can keep you from capturing the full value of the market.

With Smart Bidding Exploration, Google seems to be nudging advertisers to stop optimizing for comfort and start optimizing for growth.

Google AI Measurement Upgrades Announced At Google Marketing Live via @sejournal, @brookeosmundson

During its annual Google Marketing Live event for advertisers, Google announced upgrades to its AI measurement tools, making access easier for small brands.

These updates were shared ahead of time with Search Engine Journal during an exclusive preview event, which showcase Google’s continued investment in providing advertisers of all sizes better visibility into performance, incrementality, and return on ad spend.

Here’s what’s coming for marketers, and why you should pay attention.

Incrementality Testing: Becoming More Accessible

Measurement has always been a pain point for marketers. We spend time and budget driving performance, but often struggle to prove what’s truly moving the needle.

Historically, incrementality testing in Google Ads was only feasible for high-spending accounts, requiring at least $100K in budget to run.

That changed today, as Google is lowering the spend requirement to just $5,000 per incrementality test.

That lowered threshold opens the door for many mid-market (and even smaller) advertisers to start running controlled tests that measure the true lift driven by their ads. Not just looking at conversions that likely would’ve happened anyway.

Credit: Google

In addition to the lower threshold, Google is rolling out a new Bayesian-based methodology that increases the chances of getting conclusive results.

Tests can now run as short as 7 days or up to 56, with 28 days considered the current best practice.

With this update, marketers no longer have to rely on directional data or last-click attribution.

They’ll be able to isolate the impact of their Google Ads campaigns and adjust budgets or creative with more confidence.

Cross-Channel Measurement Is Getting Smarter Inside Google Analytics

Another big enhancement is happening within Google Analytics.

Marketers will soon be able to see more comprehensive cross-channel performance (including impressions ) across Google properties and other platforms.

The aim is to help teams better map the full customer journey and more accurately calculate ROI.

While not all of this is live just yet, Google says deeper insights are on the way in the coming months.

This should be particularly useful for brands running Performance Max or upper-funnel campaigns across multiple surfaces.

Visibility into pre-click data has historically been limited, so any lift in impression-level reporting across channels is a step forward.

Data Manager: A Central Tool For First-Party Data Activation

Google is also introducing Data Manager as a centralized tool to help marketers collect, store, and activate their first-party data . It’s got all the existing privacy protections baked in.

With the rise of privacy regulations and cookie deprecation looming, brands have been scrambling to figure out how to make better use of their owned data.

Data Manager acts as a one-stop shop, using confidential computing to ensure sensitive data stays protected and is only used for authorized purposes.

Credit: Google

Marketers can expect upcoming features like data strength recommendations, which will help identify gaps in your data strategy and offer actionable ways to improve it.

To streamline things further, Google is also launching a new Data Manager API. This update consolidates multiple APIs into a single schema, helping developers connect audience and conversion data more easily across Google Ads, GA4, and GMP.

This might not be something every marketer will use directly, but it has major implications for teams that rely on agency or partner integrations to power their campaigns.

It reduces the technical lift required to activate more first-party data signals across platforms.

Why Marketers Should Pay Attention

One of the most notable parts of this update is who these tools are built for.

In the past, many of Google’s advanced measurement tools were only accessible to advertisers with deep pockets and large internal data teams.

That left small-to-mid-sized businesses at a disadvantage when it came to proving performance or scaling their investment.

These new AI measurement tools show a clear move toward making enterprise-grade measurement more attainable for all.

For marketers under pressure to drive measurable results without doubling spend, that’s welcome news.

We’re also seeing Google start to shift more clearly toward cross-channel, privacy-safe measurement with a bigger emphasis on first-party data.

Even with all the change in direction of third-party cookie deprecation (and reversal of that decision), these tools seem to be solid building blocks that marketers can use as privacy regulations continue to adapt across the world.

Looking Ahead

The latest updates from Google Ads mark a meaningful shift toward making AI-powered measurement smarter, faster, and more accessible.

From more affordable incrementality testing to a consolidated way to activate your first-party data, these tools promise better insights without the enterprise-level budget.

Marketers still need to approach these tools with a critical eye. AI-powered doesn’t mean hands-off.

You’ll want to validate the data assumptions being used, and stay involved in shaping your own measurement strategy.

Now, it feels like marketers with modest budgets aren’t stuck on the sidelines.

Which of these new measurement tools are you looking forward to trying within your accounts?

It’s Official: Google Launches AI Max for Search Campaigns via @sejournal, @brookeosmundson

Google Ads has announced a major update to Search campaigns. The new AI Max campaign setting will roll out globally in beta starting later this month.

Per Google’s announcement, advertisers who enable AI Max in their Search campaigns can expect stronger performance through improved query matching, dynamic creative, and better control features.

According to Google, early testing shows advertisers see an average 14% more conversions or conversion value at a similar CPA or ROAS. Campaigns still using mostly exact or phrase match keywords see even greater uplifts, around 27%.

This update follows months of closed beta testing with large brands already reporting positive results.

Let’s take a deeper look at what AI Max brings and why it matters to paid search marketers.

What is AI Max for Search Campaigns?

If you’ve been hearing the term “Search Max” in the wild lately, the official name for it is AI Max for Search.

AI Max is not a new campaign type. Instead, it’s a one-click upgrade available within existing Search campaign settings.

Once activated, it layers in three core enhancements:

• Search term matching: Uses AI to extend keyword matching into relevant, high-performing queries your current keywords might miss.

• Text customization: Rebrands the former Automatically Created Assets (ACA) tool. Dynamically generates new headlines and descriptions based on your landing pages, existing ads, and keywords.

• Final URL expansion: Sends users to the most relevant pages on your site based on query intent.

Advertisers can opt out of text customization or final URL expansion at the campaign level, and opt out of search term matching at the ad group level. However, Google recommends using all three together for maximum performance.

AI Max is designed to complement, not replace, keyword match types. If a user’s search exactly matches a keyword in your campaign, that will always take priority.

Why is Google Introducing AI Max?

Search behavior is changing fast. As Google integrates more AI-powered experiences like AI Overviews and Google Lens into Search, people are using more complex, conversational, and even visual queries.

Advertisers have also voiced concerns about losing transparency and control as campaign automation expands.

AI Max aims to address both.

• Advertisers keep access to existing Search reports and controls while layering in new targeting and creative tools.
• More granular reporting is rolling out, including search terms by asset and improved URL parameters for detailed tracking.

Essentially, it’s Google’s answer to increasing demand for flexible automation, but with guardrails in place for marketers.

Are There Controls For Brand Safety?

Google added several controls to address a frequent advertiser concern: automation overreaching into irrelevant or risky placements.

Here’s what’s included with the AI Max for Search rollout:

• Brand controls: Choose which brands your ads appear alongside (or exclude specific brands).
• Location of interest controls: Target based on user geo intent at the ad group level (great for multi-location businesses).
• Creative asset controls: Remove generated assets or block them entirely if they don’t meet brand guidelines.

One note of caution: as of now, AI-generated assets will go live before advertisers have the chance to review them.

Advertisers will need to monitor and react quickly to any compliance issues.

Are There Updates Coming to Reporting?

While AI Max integrates into existing Search reporting, the functionality is bringing new insights:

• Search terms reporting will now show associated headlines and URLs.
• Asset reports will measure performance not just by impressions, but by spend and conversions.
• A new URL parameter will offer deeper visibility into search queries and performance across match types.

These reporting improvements will start in the Google Ads online interface as the feature rolls out.

Support for API, Report Editor, and Desktop Editor access is slated for later in 2025.

How Does AI Max Compare to Performance Max or Dynamic Search Ads?

Many marketers are asking how AI Max fits alongside other Google campaign types.

Here’s the current landscape of differences or overlap between other campaign types:

• Performance Max and AI Max for Search may be eligible for the same Search auctions. However, if a user’s search query exactly matches a keyword in your Search campaign, Search will always take priority.
• Dynamic Search Ads (DSA) remain available. AI Max is not a direct replacement, though it does overlap in some areas like final URL expansion and keywordless matching.
• Optimized Targeting for audiences could be seen as a similar concept to AI Max’s query expansion, but applied to audiences rather than keywords.

Additionally, AI Max for Search can be A/B tested against traditional Search setups using drafts and experiments. More customized testing tools are in development.

Who is AI Max Not Ideal For?

While AI Max offers clear benefits to trying out, this new setting may not suit every advertiser verticals.

If you’re an advertiser or a brand with the following scenarios, I’d recommend using caution when testing out AI Max for Search.

• Advertisers with strict creative guidelines or sensitive content policies.
• Brands needing pinning for ad assets (since final URL expansion does not support pinning).
• Businesses with websites that change frequently, making automated creative risky or inaccurate.

For industries like legal or healthcare, where lead quality and content compliance are crucial, AI Max may require careful testing before wide adoption.

What This Means for Search Marketers

AI Max represents a significant shift in how Google Search campaigns can scale.

It brings the adaptive reach and creative flexibility of Performance Max without requiring a new campaign type or sacrificing keyword control.

For advertisers already embracing broad match and automated bidding, AI Max may feel like a natural progression.

For those still relying on exact and phrase match keywords, it offers an opportunity to expand cautiously while maintaining key controls.

The rollout also signals Google’s direction: automation will continue to evolve, but advertiser input and oversight remain essential.

Marketers who test AI Max thoughtfully by balancing automation with strategy are likely to gain a competitive edge as search behavior grows more complex.

Channel Reporting Is Coming To Performance Max Campaigns via @sejournal, @brookeosmundson

Google just launched substantial upgrades to its Performance Max campaigns today.

In their announcement, they introduced long-anticipated reporting features that will provide advertisers with much-needed visibility into how their campaigns perform across different Google surfaces.

These updates include new channel-level reporting, full search terms data, and expanded asset performance metrics.

The goal?

It’s aimed at helping marketers better understand, evaluate, and optimize their Performance Max campaigns.

The rollout is expected to begin with an open beta for channel performance reporting in the coming weeks.

For advertisers managing budget and strategy across a mix of formats and inventory, these reporting enhancements mark a meaningful step forward in understanding where results are coming from and how to take informed action.

Advertiser Feedback is Directly Shaping PMax’s Direction

According to Google, Performance Max is now used by over one million advertisers.

In 2024 alone, Google implemented more than 90 improvements to Performance Max, leading to measurable gains in both conversions and conversion value.

But alongside performance, advertisers have consistently asked for better transparency and reporting.

Google’s latest announcements make clear that advertiser feedback has played a central role in shaping these enhancements.

The goal is to deliver clearer insights, support decision-making, and increase control—without sacrificing the benefits of automation.

Channel Performance Reporting Is Coming To Performance Max

Channel-level reporting is the most significant update in this release.

For the first time, advertisers will be able to view results by channel: Search, YouTube, Display, Discover, Gmail, Maps, and Search partners.

The new “Channel performance” page will show:

• Visual breakdowns of performance by surface
• Campaign-level metrics for each channel, including clicks, conversions, and spend
• A downloadable table with key performance data
• Diagnostics to surface missed opportunities or setup issues.

You’ll be able to find the Channel Performance reporting in the “Insights & reports” tab on the left-hand side of Google. See the example below on how the report will function.

For example, if Maps isn’t generating traffic, diagnostics might suggest adding a location asset. Or if YouTube is outperforming, advertisers can shift their focus to high-impact video creatives.

The ability to view spend and conversion value by channel adds clarity that Performance Max has previously lacked.

Search Terms Reporting Reaches (Almost) Full Visibility

Another major enhancement is the addition of full search terms reporting.

Advertisers will now be able to see the actual queries driving performance – similar to what’s available in standard Search and Shopping campaigns.

With this rollout, marketers can:

• Identify top-performing search terms
• Create tailored assets round those queries
• Apply negative keywords or brand exclusions when needed

For agencies managing multiple clients or accounts at scale, this change improves daily workflow efficiency.

Rather than relying solely on limited theme-level insights or making assumptions about what’s driving performance, teams can now analyze exact queries.

This supports better keyword refinement, more accurate exclusions, and tighter alignment between campaign objectives and user behavior, all within the familiar framework of Search best practices.

Privacy thresholds will still apply, but the reporting experience will be much more detailed than before.

At launch, this feature will be available in the Google Ads UI only, with API support expected later.

For marketers focused on search intent, this change makes Performance Max a more actionable channel.

More Granular Asset Metrics Across Campaign Types

Asset reporting is also expanding. In addition to conversion data, advertisers will now see:

• Impressions
• Clicks
• Cost
• Conversion Value

Image Credit: Google, April 2025

These new metrics will apply across Performance Max, Search, and Display. This allows advertisers to evaluate creative performance at a deeper level.

Want to know if your video is driving more conversions than your static image? Now you can. Want to see if your headline gets more clicks than your call-to-action? The data is there.

These insights support better creative testing and stronger Ad Strength scores, all based on performance—not assumptions.

Built-In Diagnostics Help Spot Gaps and Missed Opportunities

Google is also adding diagnostics that flag potential performance issues. These insights will live within the Channel performance page and highlight areas for improvement.

For example:

• If you’re not showing on Maps, diagnostics might suggest adding a location feed or location asset
• If Search delivery is limited, landing page relevance could be the cause

Image credit: Google, April 2025

This feature won’t give full control over where ads appear, but it does provide better visibility into what’s working and what’s not.

Channel exclusions are still not available in Performance Max, but Google confirmed it’s exploring future control options. For now, diagnostics serve as a step toward more informed decision-making.

Why These Updates Matter For Advertisers

This round of updates helps address a long-standing challenge with Performance Max: the lack of visibility.

Advertisers have embraced the campaign type for its scale and automation, but often struggled to understand the “how” behind performance.

With these new features, advertisers will gain:

• Channel-level transparency
• Deeper search intent insights
• Clearer creative performance metrics
• Actionable recommendations to fix delivery issues

These aren’t just incremental changes. They reshape how marketers can evaluate and optimize PMax.

The updates make it easier to align creative strategy, understand channel contribution, and refine search targeting.

It’s also clear that Google is listening. The inclusion of diagnostics, downloadable tables, and more detailed reporting shows a strong response to real-world feedback.

These updates also signal a broader industry shift toward hybrid automation models: where AI handles scale, but humans still guide strategy with the help of robust data.

As marketers continue to seek clarity on campaign performance, updates like these help reinforce trust in automated systems by making them easier to measure and manage.

More details are expected at Google Marketing Live. But this release signals a new phase for Performance Max: one that balances automation with greater accountability and insight.