May 28 2025
Is SEO Still Relevant In The AI Era? New Research Says Yes via @sejournal, @MattGSouthern

New research analyzing 25,000 user searches found that websites ranked #1 on Google appear in AI search answers 25% of the time.

This data demonstrates that traditional SEO remains relevant, despite claims that AI has rendered it obsolete.

Tomasz Rudzki, co-founder of ZipTie, studied real searches across ChatGPT, Perplexity, and Google’s AI Overviews. His findings challenge the widespread belief that AI makes traditional SEO pointless.

Top Rankings Translate To AI Visibility

The data shows a clear pattern: if you rank #1 on Google, you have a 1-in-4 chance of appearing in AI search results. Lower rankings result in lower chances.

Rudzki stated:

“The higher you rank in Google’s top 10, the more likely you are to appear in AI search results across platforms. This isn’t speculation – it’s based on real queries from real users.”

The pattern holds across all major AI search platforms, suggesting that they all rely on traditional rankings when selecting sources.

How AI Search Engines Select Sources

The study detailed how AI search operates, using information from Google’s antitrust trial. The process involves three main steps:

Step 1: Pre-selection
AI systems identify the best documents for each query, favoring pages with higher Google rankings.

Step 2: Content Extraction
The AI extracts relevant information from these top-ranking pages, prioritizing content that directly answers the user’s question.

Step 3: AI Synthesis
The AI synthesizes this information into one clear answer, utilizing Google’s Gemini model for this step.

Google’s internal documents from the trial confirmed a critical fact: using top-ranking content enhances the accuracy of AI responses, which explains why traditional rankings continue to be so significant.

The Query Fan-Out Effect Explained

Sometimes, you’ll come across sources that don’t make it into the top 10. Research identified two reasons why:

Reason 1: Personalization

Search results differ by user. A page might rank high for one user but not for another.

Reason 2: Query Fan-Out

This is the more significant factor. According to Google’s documentation:

“Both AI Overviews and AI Mode may use a ‘query fan-out’ technique — issuing multiple related searches across subtopics and data sources — to develop a response.”

Here’s what that means in simple terms:

When you search for “SEO vs SEM,” the AI discreetly runs multiple searches:

  • “What is SEO?”
  • “SEO explained”
  • “What is PP?C”
  • Plus several other related searches

Pages that perform well for these additional searches can appear in results even if they don’t rank for your primary search.

The research shows we need to think differently about content.

Traditional SEO focused on creating the “best page.” This meant comprehensive guides covering everything about a topic.

AI search wants the “best answer.” This means specific, focused responses to exact questions.

The analysis notes:

“When someone asks specifically about iPhone 15 battery life, you may rank top 1 in Google, but AI doesn’t care about it if you don’t provide a precise, relevant answer to that exact question.”

Marketers need to shift from keyword optimization to answering real questions.

Practical Implications For Digital Marketers

Here’s what marketers should do based on these findings:

  • Continue your SEO efforts: Top 10 rankings directly impact AI visibility. Do not abandon your SEO strategies.
  • Restructure your content: Divide lengthy guides into sections that address specific questions.
  • Target related searches: Optimize for various versions of your main keywords.
  • Write clearly: AI systems favor straightforward answers over content loaded with keywords.
  • Track everything: Monitor your visibility in both traditional and AI search results.

Industry Impact and Future Considerations

This research comes at the perfect time. AI search is growing rapidly. Understanding how it connects to traditional rankings gives you an edge.

Consider this: Only 25% of #1-ranked content appears in AI results. That means 75% is missing out. This suggests an opportunity for marketers who adapt.

Rudzki concludes:

“Instead of asking ‘How do I rank higher?’ start asking ‘How do I better serve users who have specific questions?’ That mindset shift is the key to thriving in the AI search era.”

For an industry experiencing rapid adoption of AI, these findings provide a strong foundation for informed strategic decisions. Instead of abandoning SEO practices, the evidence suggests building on what already works.

Featured Image: Tada Images/Shutterstock

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May 28 2025
Google’s CEO Says AI Overviews Website Referrals Are Increasing via @sejournal, @martinibuster

Google’s Sundar Pichai said in an interview that AI Overviews sends more traffic to a wider set of websites, insisting that Google cares about the web ecosystem and that he expects AI Mode to continue to send more traffic to websites, a claim that the interviewer challenged.

AI Agents Remove Customer Relationship Opportunities

There is a revolutionary change in how ecommerce that’s coming soon, where AI agents research and make purchase decisions on behalf of consumers. The interviewer brought up that some merchants have expressed concern that this will erode their ability to upsell or develop a customer relationship.

A customer relationship can be things like getting them to subscribe to an email or to receive text messages about sales, offer a coupon for a future purchase or to get them to come back and leave product reviews, all the ways that a human consumer interacts with a brand that an AI agent does not.

Sundar Pichai responded that AI agents present a good user experience and compared the AI agent in the middle between a customer and a merchant to a credit card company that sits in between the merchant and a customer, it’s a price that a merchant is willing to pay to increase business.

Pichai explained:

“I can literally see, envision 20 different ways this could work. Consumers could pay a subscription for agents, and their agents could rev share back. So you know, so that that is the CIO use case you’re talking about. That’s possible. We can’t rule that out. I don’t think we should underestimate, people may actually see more value participating in it.

I think this is, you know, it’s tough to predict, but I do think over time like you know like if you’re removing friction and improving user experience, it’s tough to bet against those in the long run, right? And so I think, in general if you’re lowering friction for it, you know, and and people are enjoying using it, somebody’s going to want to participate in it and grow their business.

And like would brands want to be in retailers? Why don’t they sell directly today? Why don’t they sell directly today? Why won’t they do that? Because retailers provide value in the middle.

Why do merchants take credit cards? There are many parts like and you find equilibrium because merchants take credit cards because they see more business as part of taking credit cards than not, right. And which justifies the increased cost of taking credit cards and may not be the perfect analogy. But I think there are all these kinds of effects going around.”

Pichai Claims That Web Ecosystem Is Growing

The interviewer began talking about the web ecosystem, calling attention to the the “downstream” effect of AI Search and AI search agents on information providers and other sites on the web.

Pichai started his answer by doing something he did in another interview about this same question where he deflected the question about web content by talking about video content.

He also made the claim that Google isn’t killing the web ecosystem and cited that the number of web pages in Google’s index has grown by 45% over the past two years, claiming it’s not AI generated content.

He said:

“I do think people are consuming a lot more information and the web is one specific format. So we should talk about the web, but zooming back out, …there are new platforms like YouTube and others too. So I think people are just consuming a lot more information, right? So it feels like like an expansionary moment. I think there are more creators. People are putting out more content, you know, and so people are generally doing a lot more. Maybe people have a little extra time in their hands. And so it’s a combination of all that.

On the web, look things have been interesting and you know we’ve had these conversations for a while, you know, obviously in 2015 there was this famous, the web is dead. You know, I always have it somewhere around, you know, which I look at it once in a while. Predictions, it’s existed for a while.

I think web is evolving pretty profoundly. When we crawl, when we look at the number of pages available to us, that number has gone up by 45% in the last two years alone. So that’s a staggering thing to think about.”

The interviewer challenged Pichai’s claim by asking if Google is detecting whether that increase in web pages is because they’re AI generated.

Pichai was caught by surprise by that question and struggled to find the answer and then finally responded that Google has many techniques for understanding the quality of web pages, including whether it was machine generated.

He doubled down on his statement that the web ecosystem is growing and then he started drifting off-topic, then he returned to the topic.

He continued:

“That doesn’t explain the trend we are seeing. So, generally there are more web pages. At an underlying level, so I think that’s an interesting phenomenom. I think everybody as a creator, like you do at The Verge, I think today if you’re doing stuff you have to do it in a cross-platform, cross-format way. So I think things are becoming more dynamic cross-format.

I think another thing people are underestimating with AI is AI will make it zero-friction to move from one format to another, because our models are multi-modal.

So I think this notion, the static moment of, you produce content by format, whereas I think machines can help translate it from, almost like different languages and they can go seamlessly between. I think it’s one of the incredible opportunities to be unlocked.

I think people are producing a lot of content, and I see consumers consuming a lot of content. We see it in our products. Others are seeing it too. So that’s probably how I would answer at the highest level.”

Related: The Data Behind Google’s AI Overviews: What Sundar Pichai Won’t Tell You

Search Traffic and Referral Patterns

The interviewer asked Pichai what his response is to people who say that AI Overviews is crushing their business.

Pichai answered:

“AI mode is going to have sources and you know, we’re very committed as a direction, as a product direction, part of why people come to Google is to experience that breadth of the web and and go in the direction they want to, right?

So I view us as giving more context. Yes, there are certain questions which may get answers, but overall that’s the pattern we see today. And if anything over the last year, it’s clear to us the breadth of where we are sending people to is increasing. And, so I expect that to be true with AI Mode as well.”

The interviewer immediately responded by noting that if everything Pichai said was true, people would be less angry with him.

Pichai dismissed the question, saying:

“You’re always going to have areas where people are robustly debating value exchanges, etc. … No one sends traffic to the web the way we do.”

See also: Google’s AI Overviews Slammed By News Publishers

Oh, Really?

What do you think? Are Google’s AI features prioritizing sending traffic to web sites?

Watch the Sundar Pichai interview here:

Featured image is screenshot from video

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May 27 2025
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

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May 27 2025
Google’s Sergey Brin Says AI Can Synthesize Top 1,000 Search Results via @sejournal, @martinibuster

Google co-founder Sergey Brin says AI is transforming search from a process of retrieving links to one of synthesizing answers by analyzing thousands of results and conducting follow-up research. He explains that this shift enables AI to perform research tasks that would take a human days or weeks, changing how people interact with information online.

Machine Learning Models Are Converging

For those who are interested in how search works, another interesting insight he shared was that algorithms are converging into a single model. In the past, Googlers have described a search engine as multiple engines, multiple algorithms, thousands of little machines working together on different parts of search.

What Brin shared is that machine learning algorithms are converging into models that can do it all, where the learnings from specialist models are integrated into the more general model.

Brin explained:

“You know, things have been more converging. And, this is sort of broadly through across machine learning. I mean, you used to have all kinds of different kinds of models and whatever, convolutional networks for vision things. And you know, you had… RNN’s for text and speech and stuff. And, you know, all of this has shifted to Transformers basically.

And increasingly, it’s also just becoming one model.”

Google Integrates Specialized Model Learnings Into General Models

His answer continued, shifting to explaining how it’s the usual thing that Google does, integrating learnings from specialized models into more general ones.

Brin continued his answer:

“Now we do get a lot of oomph occasionally, we do specialized models. And it’s it’s definitely scientifically a good way to iterate when you have a particular target, you don’t have to, like, do everything in every language, handle whatever both images and video and audio in one go. But we are generally able to. After we do that, take those learnings and basically put that capability into a general model.”

Future Interfaces: Multimodal Interaction

Google has recently filed multiple patents around a new kind of visual and audio interface where Google’s AI can take what a user is seeing as input and provide answers about it. Brin admitted that their first attempt at doing that with Google Glasses was premature, that the technology for supporting that wasn’t mature. He says that they’ve made progress with that kind of searching but that they’re still working on battery life.

Brin shared:

“Yeah, I kind of messed that up. I’ll be honest. Got the timing totally wrong on that.

There are a bunch of things I wish I’d done differently, but honestly, it was just like the technology wasn’t ready for Google Glass.

But nowadays these things I think are more sensible. I mean, there’s still battery life issues, I think, that you know we and others need to overcome, but I think that’s a cool form factor.”

Predicting The Future Of AI Is Difficult

Sergey Brin declined to predict what the future will be like because technology is moving so fast.

He explained:

“I mean when you say 10 years though, you know a lot of people are saying, hey, the singularity is like, right, five years away. So your ability to see through that into the future, I mean, it’s very hard”

Improved Response Time and Voice Input Are Changing Habits

He agreed with the interviewers that improved response time to voice input are changing user habits, making real-time verbal interaction more viable. But he also said that voice mode isn’t always the best way to interface with AI and used the example of a person talking to a computer at work as a socially awkward application of voice input. This is interesting because we think of the Star Trek Computer voice method of interacting with a computer but what it would get quite loud and distracting if everyone in an office were interacting audibly with an AI.

He shared:

“Everything is getting better and faster and so for you know, smaller models are more capable. There are better ways to do inference on them that are faster.

We have the big open shared offices. So during work I can’t really use voice mode too much. I usually use it on the drive.

I don’t feel like I could, I mean, I would get its output in my headphones, but if I want to speak to it, then everybody’s listening to me. So I just think that would be socially awkward. …I do chat to the AI, but then it’s like audio in and audio out. Yeah, but I feel like I honestly, maybe it’s a good argument for a private office.”

AI Deep Research Can Synthesize Top 1,000 Search Results

Brin explained how AI’s ability to conduct deep research, such as analyzing massive amounts of search results and conducting follow-up research changes what it means to do search. He described a shift in search that changes the fundamental nature of search from retrieval (here are some links, look at them) to generating insights from the data (here’s a summary of what it all means, I did the work for you).

Brin contrasted what he can do manually with regular search and what AI can do at scale.

He said:

“To me, the exciting thing about AI, especially these days, I mean, it’s not like quite AGI yet as people are seeking or it’s not superhuman intelligence, but it’s pretty damn smart and can definitely surprise you.

So I think of the superpower is when it can do things in the volume that I cannot. So you know by default when you use some of our AI systems, you know, it’ll suck down whatever top ten search results and kind of pull out what you need out of them, something like that. But I could do that myself, to be honest, you know, maybe take me a little bit more time.

But if it sucks down the top, you know thousand results and then does follow-on searches for each of those and reads them deeply, like that’s, you know, a week of work for me like I can’t do that.”

AI With Advertising

Sergey Brin expressed enthusiasm for advertising within the context of the free tier of AI but his answer skipped over that, giving the indication that this wasn’t something they were planning for. He instead promoted the concept of providing a previous generation model for free while reserving the latest generation model for the paid tiers.

Sergey explained:

“Well, OK, it’s free today without ads on the side. You just got a certain number of the Top Model. I think we likely are going to have always now like sort of top models that we can’t supply infinitely to everyone right off the bat. But you know, wait three months and then the next generation.

I’m all for, you know, really good AI advertising. I don’t think we’re going to like necessarily… our latest and greatest models, which are you, know, take a lot of computation, I don’t think, we’re going to just be free to everybody right off the bat, but as we go to the next generation, you know, it’s like every time we’ve gone forward a generation, then the sort of the new free tier is usually as good as the previous pro tier and sometimes better.”

Watch the interview here:

Sergey Brin, Google Co-Founder | All-In Live from Miami

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May 26 2025
Google’s New AI Tools Promise Faster Ads, But Raise Control Concerns via @sejournal, @MattGSouthern

Google’s latest AI tools promise to manage campaigns automatically. But advertisers are asking whether these new features give up too much human control.

At Google Marketing Live, the company showcased three new AI agents. These tools can handle everything from creating campaigns to managing tasks across multiple platforms.

However, the announcement raised questions from attendees about accountability and transparency.

The reaction highlights growing tension in the industry. Platforms want more automation, while marketers worry about losing control of their accounts.

What Google Introduced

1. Google Ads Agentic Expert

This system makes changes to your campaigns without first asking for permission. It can:

  • Create multiple ad groups with matching creative assets
  • Add keywords and implement creative suggestions
  • Fix policy issues and submit appeals
  • Generate reports and answer campaign questions

2. Google Analytics Data Expert

This tool finds insights and trends automatically. It also makes data exploration easier through simple visuals.

The goal is to help marketers spot performance patterns without deep Analytics knowledge.

3. Marketing Advisor Chrome Extension

This browser extension launches later this year. It manages tasks across multiple platforms, including:

  • Automated tagging and tag installation
  • Seasonal trend analysis
  • Problem diagnosis across different sites

Marketing Advisor works across Google properties like Google Ads and Analytics. It also works on external websites and content management systems.

Here’s a promotional video demonstrating these tools’ capabilities:

Where Advertisers Push Back

During a press session led by Melissa Hsieh Nikolic, Director of Product Management for YouTube Ads, and Pallavi Naresh, Director of Product Management for Google Ads, executives addressed concerns from industry professionals.

Control and Change Tracking Issues

Advertisers asked how AI-made changes would appear in Google Ads’ change history, but executives couldn’t give clear answers.

Naresh responded:

“That’s a great question. I don’t know if it’ll show up with your username or like you and the agent’s username.”

This uncertainty worries agencies and brands. They need detailed records of campaign changes for client reports and internal approvals.

One attendee directly questioned the automation direction, stating:

“We’ve seen the ‘googlification’ of the Google help desk. Getting to a human is hard. This seems like it’s going down the path of replacing that.”

Google reps promised human support would stay available, responding:

“That’s not the intention. You will still be able to access support in the ways you can today.”

Transparency and Content Labeling Gaps

The new AI creative tools raised questions about content authenticity.

Google introduced image-to-video creation and “outpainting” technology. Outpainting expands video content for different screen sizes. However, Google’s approach to AI content labeling differs from other platforms.

Hsieh Nikolic explained:

“All of our images are watermarked with metadata and SynthID so generated content can be identified. At this time, we’re not labeling ads with any sort of identification.”

This approach is different from other platforms that use visible AI content labels.

Performance Claims & Industry Context

Google shared performance data for its AI-enhanced tools. Products with AI-generated images saw a “remarkable 20% increase on return on ad spend” compared to standard listings.

The company also said “advertiser adoption of Google AI for generating creative increased by 2500%” in the past year. But this growth comes with the control concerns mentioned above.

Google revealed it’s “actively working on a generative creative API.” This could impact third-party tools and agency workflows.

The timing makes sense given industry pressures. Google says marketers spend “10 hours or more every week creating visual content.” These tools directly address that pain point.

What This Means for Digital Marketing

The three-agent system is Google’s biggest push into hands-off advertising management yet. It moves beyond creative help to full campaign control.

Digital marketing has always been about precise budget and targeting control. This shift toward AI decision-making changes how advertisers and platforms work together.

The pushback from advertisers suggests more resistance than Google expected. This is especially true around accountability and transparency, which agencies and brands need for client relationships.

The Marketing Advisor Chrome extension is particularly ambitious. It extends Google’s reach beyond its platforms into general marketing workflow management, which could reshape how digital marketing teams work across the industry.

What Marketers Should Do

Set Up AI Change Protocols

As these features roll out, advertisers should:

  • Create clear rules for AI-driven campaign changes
  • Make sure approval processes can handle automated changes
  • Develop documentation requirements for AI modifications

Demand Clear Tracking

The change history question is still unresolved. It’s critical for agencies and brands that need detailed campaign records. Marketers should:

  • Ask for specific details about change tracking before using agentic features
  • Create backup documentation processes for AI modifications
  • Clarify how automated changes will show in client reports

Prepare for API Changes

Google is developing a generative creative API. Marketing teams should think about how this might impact:

  • Existing third-party tool connections
  • Agency workflow automation
  • Custom reporting systems

Closing Thoughts

Google’s three-agent system shows the company’s confidence in AI-driven advertising management. It builds on the success of over 500,000 advertisers using conversational AI features.

However, industry practitioners’ concerns highlight real challenges around control, transparency, and technical readiness. As these tools become standard practice, these issues need solutions.

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May 22 2025
Google Claims AI Search Delivers ‘Quality Clicks’ Despite Traffic Loss via @sejournal, @MattGSouthern

Google executives are trying to reframe the conversation about AI-powered search features as industry data reveals significant website traffic reductions.

During a recent Google Marketing Live press session, executives indicated that while clicks may be down, the visits that do happen are supposedly of higher quality.

The session featured a panel including Jenny Cheng, Vice President and General Manager of Google’s Merchant Shopping organization; Sean Downey, President of Americas & Global Partners at Google; and Nicky Rettke, YouTube Vice President of Product Management.

Photo: Matt G. Southern / Search Engine Journal

Traffic Quality vs. Quantity Debate

Independent studies have documented that pages with AI overviews in search results receive significantly fewer clicks on organic listings than traditional search results.

When confronted with this issue, a Google executive sidestepped direct traffic concerns by shifting focus to user behavior, stating:

“What we’re seeing is people asking more questions. So they’ll ask a first question, they’ll get information and then go and ask a different question. So they’re refining and getting more information and then they’re making a decision of what website to go to.”

Google pointed to a 10% increase in queries from AI-enhanced search.

Google’s narrative suggests these changes benefit everyone:

“When they get to a decision to click out, it’s a more highly qualified click… What we hope to see over time—and we don’t have any data to share on this—is more time spent on site, which is what we see organically in a much more highly qualified visitor for the website.”

The notable admission that Google has “no data to share” on these quality improvements leaves their claims unverified.

Ads Perform Differently Than Organic Content

While publishers grapple with declining traffic, Google insists that ad performance remains largely unchanged in AI-enhanced search:

“When we run ads on AI overviews versus ads on standard search, we see pretty much the same level of monetization capabilities, which would indicate most factors are the same and they’re producing really the same results for advertisers to date.”

This favorable situation suggests that Google’s ad revenue may stay stable while organic traffic patterns shift, potentially pressuring more publishers to adopt paid strategies to maintain visibility.

New Search Patterns Demand Content Adaptation

Google executives characterized the evolution of search as a response to user preferences for more conversational and multimodal queries, stating:

“What we’re trying to do when we release things like AI overviews or AI mode is we’re trying to give consumers new ways to discover information and get answers to their most important questions… Most humans have unbound curiosity and their context strings or their query strings are much more conversational.”

For SEO professionals, Google recommends accommodating these changes by:

  • Creating content that directly answers user questions
  • Adding more video content
  • Developing detailed FAQs and Q&A sections

AI Mode Creates New Discovery Opportunities?

Google also presented its AI mode as a potential way to increase content discovery through what they termed a “fanning technique.”

They explained:

“When we get into AI mode, it’s a similar functionality because we are also doing the fanning technique where you’re having many more queries go out. If you ask the question, it’s looking at a variety of different versions of that, which is giving more websites a chance to be considered.

We’re researching more sites, pulling in more information from more sites and summarizing. And that’s more linked opportunities for the publishers as well as the sites that are pushing the content to have access to it.”

Whether these theoretical opportunities translate to actual traffic remains to be seen.

Measurement Challenges

For marketers, the situation is complicated because Google’s reporting systems don’t differentiate between clicks from traditional search, AI overviews, and AI mode.

When asked if these different placements are shown separately in ad reporting, the Google representatives confirmed:

“We do not. Within the search term reporting, they’re not specifically broken out by the placement in that way. And that’s because the reporting is tied to what’s actionable for advertisers.”

This lack of transparency makes it impossible for publishers to verify Google’s claims independently.

The Road Ahead

While Google presents an optimistic view of traffic quality from AI-enhanced search, the lack of specific data places marketers in a precarious position.

Publishers and SEO professionals must now create their own measurement methods to assess whether these allegedly “more qualified clicks” truly offer greater value despite their reduced numbers.

For now, content creators are being asked to adjust their strategies to align with Google’s vision while having little choice but to accept the company’s quality claims on faith alone.

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May 21 2025
Google’s Official Advice On Optimizing For AI Overviews & AI Mode via @sejournal, @MattGSouthern

Google has released new guidelines for website owners who want to excel in AI-powered search.

In a blog post, Search Advocate John Mueller shared tips for ranking in AI Overviews and AI Mode.

This guidance comes as Google moves beyond traditional “blue links” to offer more AI-driven search features.

AI Is Changing Search Behavior

Google noted that users now ask longer questions and follow-up queries through these new interfaces, which creates challenges and opportunities for publishers.

Mueller writes:

“The underpinnings of what Google has long advised carries across to these new experiences. Focus on your visitors and provide them with unique, satisfying content.”

Content Quality Remains Paramount

Google says creating “unique, non-commodity content” is still the foundation for success in all search formats, including AI.

The company recommends focusing on content that meets user needs instead of trying to trick the algorithm.

Google points out that AI search users ask more specific questions and follow-ups. This suggests that thorough, detailed content works especially well in these new search environments.

Technical Requirements and Page Experience

Beyond good content, Google stressed the importance of technical access.

This includes ensuring that:

  • Googlebot isn’t blocked
  • Pages load correctly
  • Content can be indexed

Also focus on user experience factors like mobile-friendly design, fast loading speeds, and clear main content.

Mueller writes in the blog post:

“Even the best content can be disappointing to people if they arrive at a page that’s cluttered, difficult to navigate or makes it hard to find the main information they’re seeking. Ensure that you’re providing a good page experience for those who arrive either from classic or AI search results…”

Managing Content Visibility In AI Experiences

Google confirms that current content controls work for AI search.

Publishers can use the following tags to control how their content appears:

  • nosnippet
  • data-nosnippet
  • max-snippet
  • noindex

More restrictions will limit visibility in AI results.

Multimedia Content For Multimodal Search

Google’s blog post stressed the growing importance of images and videos as Google’s AI improves.

With multimodal search, you can upload images and ask questions about them. Google recommends adding high-quality visuals to support your text content.

Ecommerce businesses should keep their Merchant Center and Business Profile information updated for better performance in visual searches.

Rethinking Success Metrics

Google shared insights about user behavior with AI search results, suggesting publishers may need to reconsider how they measure success:

“We’ve seen that when people click to a website from search results pages with AI Overviews, these clicks are higher quality, where users are more likely to spend more time on the site.”

Google suggests AI results provide better context about topics, potentially sending more engaged website visitors.

Mueller encourages site owners to look beyond just clicks and focus on more meaningful metrics like sales, signups, and engagement.

What This Means

This guidance shows that while search looks different now, Google’s main ranking principles haven’t changed.

Unique content, technical quality, and user experience still define success, even as AI changes how people use search.

The key takeaways are:

  • Your website meets the technical requirements for Google Search
  • Optimize your images and videos
  • Review your meta directives
  • Rethink how you measure traffic quality from AI search rather than just counting clicks.

Google’s full guidance, along with additional resources on AI features and generative AI content, can be found on the Google Search Central blog.

Featured Image: bluestork/Shutterstock

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May 21 2025
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.

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May 21 2025
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?

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May 21 2025
30-Year SEO Pro Shows How To Adapt To Google’s Zero-Click Search via @sejournal, @martinibuster

Search marketer Michael Bonfils recently discussed how AI is disrupting search marketing and shared insights into what he feels is an appropriate response to one of the most difficult search environments he’s seen in his thirty years of experience.

Michael Bonfils (LinkedIn profile) has worked in digital marketing since virtually the dawn of it all, well before Google even existed. He’s a leading international digital marketer with experience across every aspect of digital marketing, from on-page SEO to digital advertising. Michael joined Gianluca Fiorelli (LinkedIn profile) on the Advanced Web Ranking podcast and shared his insights on the challenges AI is bringing to digital marketing and novel ideas for how to navigate them.

Brutal Environment For Digital Marketing

Gianluca mentioned there’s a perception gap with AI where on one side are marketers who are heralding the end of SEO and PPC and on the other side are the “AI bros” who cheerlead that everything is going to become even better, with better leads from ChatGPT, etc.

He shook his head and said:

“It’s neither going to be a disaster and it’s neither going to be an AI paradise.”

Gianluca asked him what trends he’s seeing. Michael responded that the trends he’s seeing is that click volume has gone down since the introduction of AI. He said during other times when volume is down the click through rates go up, like during the pandemic. But that’s not happening now. Click through rates are down, volume is down but Cost Per Clicks are at historic highs.

Michael observed,

“But now, …the level we’re at now is the worst time since 2019 during the pandemic and prior to that it was never that bad.

…If you want throw the CPC factor in, the CPC’s are historically higher than they have been for years. So now we’ve got this perfect problem, click through rates down, volume down, CPC’s up. What does that mean? ROI is getting hit and clients are leaning on organic to try to make up for whatever shortfall there is and they can’t find it, they can’t find the traffic.

So to answer your question, …now that we’re going into Europe with AI overviews, are they impacting things? One hundred percent. And they’ll continue to change. “

Later on they discussed how a lot of what Google is doing is reactionary, a response to external pressures from companies like Perplexity AI and OpenAI, and the search industry is caught in the middle of it.

AI Overviews Leads To Loss Of Strategic Data

Michael Bonfils discusses how AI overviews leads to zero-click behavior and while most SEOs stop right there, Michael points out that this situation affects the data that’s available to marketers and as a consequence impacts content strategy.

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