Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision over previous methods, with successful testing in scaled applications such as spam detection in ads.
The announcement of this new technology is referred to as expanding the boundaries of what has been possible up to today:
“Today, we explore the possibility of designing a single model that can excel on interconnected relational tables and at the same time generalize to any arbitrary set of tables, features, and tasks without additional training. We are excited to share our recent progress on developing such graph foundation models (GFM) that push the frontiers of graph learning and tabular ML well beyond standard baselines.”
Graph Neural Networks Vs. Graph Foundation Models
Graphs are representations of data that are related to each other. The connections between the objects are called edges and the objects themselves are called nodes. In SEO, the most familiar type of graph could be said to be the Link Graph, which is a map of the entire web by the links that connect one web page to another.
Current technology uses Graph Neural Networks (GNNs) to represent data like web page content and can be used to identify the topic of a web page.
A Google Research blog post about GNNs explains their importance:
“Graph neural networks, or GNNs for short, have emerged as a powerful technique to leverage both the graph’s connectivity (as in the older algorithms DeepWalk and Node2Vec) and the input features on the various nodes and edges. GNNs can make predictions for graphs as a whole (Does this molecule react in a certain way?), for individual nodes (What’s the topic of this document, given its citations?)…
Apart from making predictions about graphs, GNNs are a powerful tool used to bridge the chasm to more typical neural network use cases. They encode a graph’s discrete, relational information in a continuous way so that it can be included naturally in another deep learning system.”
The downside to GNNs is that they are tethered to the graph on which they were trained and can’t be used on a different kind of graph. To use it on a different graph, Google has to train another model specifically for that other graph.
To make an analogy, it’s like having to train a new generative AI model on French language documents just to get it to work in another language, but that’s not the case because LLMs can generalize to other languages, which is not the case for models that work with graphs. This is the problem that the invention solves, to create a model that generalizes to other graphs without having to be trained on them first.
The breakthrough that Google announced is that with the new Graph Foundation Models, Google can now train a model that can generalize across new graphs that it hasn’t been trained on and understand patterns and connections within those graphs. And it can do it three to forty times more precisely.
Announcement But No Research Paper
Google’s announcement does not link to a research paper. It’s been variously reported that Google has decided to publish less research papers and this is a big example of that policy change. Is it because this innovation is so big they want to keep this as a competitive advantage?
How Graph Foundation Models Work
In a conventional graph, let’s say a graph of the Internet, web pages are the nodes. The links between the nodes (web pages) are called the edges. In that kind of graph, you can see similarities between pages because the pages about a specific topic tend to link to other pages about the same specific topic.
In very simple terms, a Graph Foundation Model turns every row in every table into a node and connects related nodes based on the relationships in the tables. The result is a single large graph that the model uses to learn from existing data and make predictions (like identifying spam) on new data.
Screenshot Of Five Tables
Image by Google
Transforming Tables Into A Single Graph
The research paper says this about the following images which illustrate the process:
“Data preparation consists of transforming tables into a single graph, where each row of a table becomes a node of the respective node type, and foreign key columns become edges between the nodes. Connections between five tables shown become edges in the resulting graph.”
Screenshot Of Tables Converted To Edges
Image by Google
What makes this new model exceptional is that the process of creating it is “straightforward” and it scales. The part about scaling is important because it means that the invention is able to work across Google’s massive infrastructure.
“We argue that leveraging the connectivity structure between tables is key for effective ML algorithms and better downstream performance, even when tabular feature data (e.g., price, size, category) is sparse or noisy. To this end, the only data preparation step consists of transforming a collection of tables into a single heterogeneous graph.
The process is rather straightforward and can be executed at scale: each table becomes a unique node type and each row in a table becomes a node. For each row in a table, its foreign key relations become typed edges to respective nodes from other tables while the rest of the columns are treated as node features (typically, with numerical or categorical values). Optionally, we can also keep temporal information as node or edge features.”
Tests Are Successful
Google’s announcement says that they tested it in identifying spam in Google Ads, which was difficult because it’s a system that uses dozens of large graphs. Current systems are unable to make connections between unrelated graphs and miss important context.
Google’s new Graph Foundation Model was able to make the connections between all the graphs and improved performance.
The announcement described the achievement:
“We observe a significant performance boost compared to the best tuned single-table baselines. Depending on the downstream task, GFM brings 3x – 40x gains in average precision, which indicates that the graph structure in relational tables provides a crucial signal to be leveraged by ML models.”
Is Google Using This System?
It’s notable that Google successfully tested the system with Google Ads for spam detection and reported upsides and no downsides. This means that it can be used in a live environment for a variety of real-world tasks. They used it for Google Ads spam detection and because it’s a flexible model that means it can be used for other tasks for which multiple graphs are used, from identifying content topics to identifying link spam.
Normally, when something falls short the research papers and announcement say that it points the way for future but that’s not how this new invention is presented. It’s presented as a success and it ends with a statement saying that these results can be further improved, meaning it can get even better than these already spectacular results.
“These results can be further improved by additional scaling and diverse training data collection together with a deeper theoretical understanding of generalization.”
The AI search revolution has arrived with fanfare, transforming how users discover information across platforms like ChatGPT, Perplexity, and Google’s AI Overviews.
Yet, beneath the headlines lies a counterintuitive reality that’s reshaping how we approach the age-old debate and strategies on desktop vs. mobile: Over 90% of AI-powered search referrals originate from desktop devices.
While mobile accounts for more than half of global web traffic, AI search engines are making their biggest impact on desktop – a complete reversal of typical user behavior patterns that creates both challenges and more mobile opportunities for marketers.
Currently, some of the findings I share below contradict conventional wisdom.
Recent analysis of referral traffic across leading AI search platforms in the U.S. and Europe shows a striking disconnect between where users consume content and where AI engines drive meaningful traffic.
This gap represents one of the most significant untapped opportunities in the current search landscape.
AI Desktop Vs. Mobile Referral Numbers Tell A Surprising Story
The data from BrightEdge Generative Parser (my employer for disclosure) paints a clear picture of desktop dominance across virtually every AI-powered search platform.
ChatGPT leads the desktop concentration, with 94% of referral traffic coming from desktop devices, leaving just 6% for mobile users. This massive skew occurs despite ChatGPT’s widespread mobile app adoption.
Perplexity pushes desktop dominance even further, with 96.5% of referrals originating from desktop and mobile barely registering at 3.4%. For a platform positioning itself as a research-focused AI engine, this pattern suggests that users prefer desktop environments for gathering in-depth information.
Microsoft’s Bing maintains similar patterns, with 95% of desktop referrals vs. 4% mobile, despite integration across Microsoft’s ecosystem and the introduction of Copilot features.
Google Gemini follows suit, with 91% of traffic coming from desktop and 5% from mobile, indicating that even Google’s AI offerings struggle to capture mobile referral momentum.
The lone exception? Google Search itself maintains the mobile majority at 53% mobile vs. 44% desktop, but this reflects its entrenched position as the default search engine across mobile browsers, particularly Safari on iPhones.
Source: BrightEdge The Open Frontier of Mobile AI Search, June 2025
Why Mobile AI Search Isn’t Converting To Referrals
The disparity isn’t about user engagement; AI search activity on mobile is likely booming.
Instead, it’s about architectural design choices that fundamentally alter user flows and referral patterns.
The In-App Preview Problem
Mobile AI platforms often intercept the first click on citations, showing content previews within their own interfaces.
This creates a multi-step process where users must click again to reach external websites, significantly reducing referral traffic compared to desktop experiences, where first clicks typically lead directly to source sites.
ChatGPT exemplifies this pattern. On desktop, citation clicks immediately redirect users to source websites. On mobile, the app frequently displays in-app content previews, requiring users to take additional action to generate actual referrals.
The Discovery Vs. Research Divide
Desktop and mobile AI searches serve fundamentally different user intents.
Mobile users often engage in discovery-oriented searches, seeking quick answers, product comparisons, and immediate problem-solving.
Desktop users tend to gravitate toward comprehensive research, detailed analysis, and tasks that require sustained attention.
This behavioral split suggests AI platforms are evolving into distinct experiences rather than responsive versions of the same product.
Google’s AI Overviews demonstrate this evolution clearly: Ecommerce queries are three times more likely to trigger mobile AI Overviews (13.5% vs. 4.5% on desktop), treating shopping searches as educational discovery rather than direct product promotion.
Meanwhile, desktop AI Overviews command 80% more screen real estate (1110 px vs. 617 px) and appear for 39% more keywords than mobile devices, but show more consistent day-to-day patterns.
This suggests Google is actively experimenting with mobile AI formats while maintaining predictable desktop experiences.
The Apple Factor: Mobile’s Hidden Gatekeeper
Apple’s role as mobile web gatekeeper cannot be understated.
With Safari as the default browser on nearly a billion devices, Apple controls mobile search behavior in ways that could reshape the entire landscape overnight.
Current data shows that 58% of Google’s mobile search traffic to brand websites originates from iPhones, making Apple’s browser defaults critically important for AI search adoption.
Unlike Google, which has integrated AI features across its mobile search experience, Apple has not yet embedded AI-powered search into its mobile web stack.
This creates a massive structural opportunity. A single change in Safari’s default search provider or the introduction of native AI search features could trigger a significant redistribution of AI-powered traffic across the mobile ecosystem.
As mobile AI platforms mature and address current referral limitations, early movers will capture significant advantages.
Build Mobile AI Foundations Today
Responsive design excellence becomes critical when AI engines start citing mobile content more frequently.
Ensure your site adapts seamlessly across various screen sizes, orientations, and device modes to maximize citation potential regardless of how AI platforms display your content.
Optimize for speed and accessibility with fast page load times and mobile-friendly content that includes appropriately sized text, images, and interactive elements.
We are seeing AI engines increasingly factor user experience signals into their citation decisions. Schema markup is recommended so AI engines can interpret the structured data on your mobile pages and present users with content that they need and want.
Improve Core Web Vitals as these metrics become crucial for mobile AI performance. Core Web Vitals measure webpage quality beyond loading speed, correlating directly with user experience.
For mobile AI optimization, every millisecond matters – small improvements can have a significant impact on citation likelihood.
Track Desktop Vs. Mobile AI Performance
Monitor AI Overview differences using keyword reporting tools that switch between desktop and mobile AI Overviews.
This enables you to observe performance gaps and identify platform-specific opportunities.
The data reveals striking differences:
Desktop AI Overviews claim 80% more screen real estate (1110 px vs. 617 px), allowing for more detailed explanations and citation opportunities.
Desktop shows 39% more keyword coverage than mobile devices, but this gap represents a future mobile opportunity.
Ecommerce queries are three times more likely to trigger mobile AI Overviews, as platforms treat shopping searches as educational discovery on mobile.
Source: BrightEdge, May 2025
Have Different Content Strategies For Both Desktop And Mobile
Create mobile-first educational content and product guides rather than traditional product pages.
Mobile AI engines favor discovery-oriented content that helps users understand products and make informed decisions.
Ensure dual-platform accessibility by configuring your site’s crawling capabilities for both mobile and desktop views. Your content must be prepared for AI citation regardless of screen size or platform interface.
Watch Apple and Google industry moves: With Apple’s potential entry into AI search, content strategies should account for possible Safari integration changes that could dramatically shift mobile search behavior overnight.
3. Leveraging The Current Desktop Opportunity
While mobile AI search matures, desktop presents immediate opportunities for brands ready to optimize for AI-powered referrals.
Desktop AI citation optimization: Focus on creating quotable, authoritative content that AI engines can easily cite and reference. This includes structured data markup, clear section headers, and direct answers to common questions.
Comprehensive content development: Desktop AI users engage with longer-form, detailed content. Invest in comprehensive guides, thorough analysis, and expert commentary that support extended research sessions.
Multi-modal content integration: Desktop environments support richer media experiences. Combine text, video, infographics, and interactive elements to increase citation potential across different AI platforms.
More Mobile AI Disruption Is Coming
The current 90% desktop dominance in AI referrals represents a temporary market imbalance rather than a permanent shift away from mobile. Several factors suggest significant mobile AI search growth ahead.
Platform incentives align toward mobile expansion. AI search companies understand that capturing mobile market share is essential for long-term growth, and current referral limitations likely drive the active development of mobile-optimized solutions.
User behavior patterns favor mobile AI adoption. Once technical barriers to mobile AI referrals are addressed, user preferences for mobile-first interactions should drive rapid adoption.
Apple’s AI integration timeline creates a sense of urgency. With Apple controlling mobile browser defaults and reportedly developing AI search capabilities, the mobile AI landscape could transform rapidly.
Key Takeaways
The AI search revolution is creating two distinct experiences: desktop-focused referral traffic and mobile-focused engagement that don’t yet translate to website visits. This divide presents both immediate opportunities and strategic imperatives for marketers:
Immediate opportunities exist in desktop AI optimization. With 90% of AI referrals coming from desktops, brands can capture significant traffic by optimizing for desktop AI search patterns and citation preferences.
Mobile AI strategy requires different thinking. Mobile AI optimization isn’t about responsive design. It’s about understanding discovery-focused user intent and preparing for different referral mechanisms as more AI search engines hit the market.
Apple remains the wild card. Any changes to Safari’s default search behavior or introduction of native AI features could reshape mobile search overnight, making preparation essential.
The brands that recognize this desktop-mobile divide and develop device-specific AI strategies will gain significant competitive advantages as the AI search ecosystem matures.
The question isn’t whether mobile AI search will grow. It’s whether your plan will be ready when it does.
The future of AI search lies not in choosing between desktop and mobile but in mastering both experiences as distinct opportunities to serve different user needs and capture referral traffic across the entire search journey.
Unless otherwise indicated, any data mentioned above was taken from this BrightEdge study. The data was for May 2025 and is based on thousands of actual website referrals for medium to large brands across the world.
Google’s John Mueller and Martin Splitt discussed the problem of how to approach content for achieving business goals, the wisdom of setting expectations, and observed that it may not matter whether a site is optimized if the content is already achieving its intended results.
Getting The Content Right
Anyone can write, but it’s hard to communicate in a way that meets the audience’s needs. One thing SEOs often get wrong is content, which remains the most important ranking factor in modern search engines.
A common mistake is publishing entire sentences that waste time. I think that happens when writers are trying to meet an arbitrary word count and providing context for the high volume keywords they want to rank for.
Martin Splitt started the discussion by asking how to go about writing content and shared his own experience writing content and getting it wrong because he was writing for himself and not for what the audience needs to read.
Splitt shared:
“…how would I know how to go about content? Because now I know who I want to address and probably also roughly what I want to do. But, I mean, that’s a whole different skillset, right? That’s like copywriting and probably some researching and maybe some lettering and editing, and wow. That’s a lot. I love to write. I love to write.
…But I love having a technical writer on the team. Lizzi is a tremendous help with anything that is writing. I honestly thought I’m a good, reasonably good writer. And then Lizzi came and asked three questions on a piece of documentation that I thought was almost perfect.
I basically started questioning the foundations of the universe because I was like, “Okay, no, this document doesn’t even make sense. I haven’t answered the fundamental questions that I need to answer before I can even start writing. I’ve written like three pages.
Holy moly, that is a skill that is an amazingly tricky skill to acquire, I think. How do I start writing? Just write what I think I should be writing, I guess.”
Writing is easy to do, but difficult to do well. I’ve seen many sites that have the SEO fundamentals in place, but are undermined by the content. Splitt’s experience highlights the value in getting a second opinion on content.
Site Visitors Are Your Inspiration
Mueller and Splitt next move on to the topic of what publishers and SEOs should write about it and their answer is to focus on what users want, encouraging to do something as simple as asking their readers or customers.
Mueller observed:
“I think, if you have absolutely no inspiration, one approach could be to ask your existing customers and just ask them like:
How did you find me?
What were you looking for?
Where were you looking?
Were you just looking on a map? What is it that brought you here?
This is something that you can ask anyone, especially if you have a physical business.
..It’s pretty easy to just ask this randomly without scaring people away. That’s kind of one aspect I would do and try to build up this collection of ‘these are different searches that people have done in different places, maybe on different systems, and I want to make sure I’m kind of visible there.’”
Set Reasonable Expectations
John Mueller and Martin Splitt next provide a reality check on the keyword phrases that publishers and SEOs choose to optimize for. It’s not always about the difficulty of the phrases; it’s also about how relevant they are to the website.
Mueller commented about what to do with the keyword phrases that are chosen for targeting:
“And then I would take those and just try them out and see what comes up, and think about how reasonable it would be for one of your pages, perhaps to show up there and how reasonable it can be, I think is something where you have to be brutally honest with yourself, because it’s sometimes tempting to say, “Well, I would like to appear first for the search bookstore on the internet.” Probably that’s not going to happen. I mean, who knows? But there’s a lot of competition for some of these terms.
But, if you’re talking about someone searching for bookstores or bookstores in Zurich or bookstores on Maps or something like that, then that’s a lot more well defined and a lot easier for you to look at and see, what are other people doing there? Maybe my pages are already there. And, based on that, you can try to build out, what is it that I need to at least mention on my pages.”
Mueller followed up by downplaying whether a site is search optimized or not, saying that what’s important is if the site is performing as well as intended. Whether or not it’s properly optimized doesn’t matter if it’s already doing well as it is. Some may argue that the site could be doing better, but that’s outside of the context of what Mueller was commenting on. Mueller’s context was a business owner who was satisfied with the performance of the site.
Mueller observed:
“I mean, it all depends on how serious you take your goal, right? If you’re like a small local business you’re saying, ‘Well, I have a website and I hear I should make it SEO, but I don’t really care.’ Then it’s like do whatever you want kind of thing. If you have enough business and you’re happy. There’s no one to judge you to say, “Your website is not SEO optimized.”
Listen to Episode 95 of the Search Off The Record at about the ten minute mark:
Google’s Search Off The Record podcast discussed when a business should hire an SEO consultant and what metrics of success should look like. They also talked about a red flag to watch for when considering a search marketer.
Hire An SEO When It Becomes Time Consuming
Martin Splitt started the conversation off by asking at what point a business should hire an SEO:
“…I know people are hiring agencies and SEO experts. When is the point where you think an expert or an agency should come in? What’s the bits and pieces that are not as easy to do while I do my business that I should have an expert for?”
John replied that there is no one criteria or line to cross at which point a business should hire a consultant. He did however point out that there comes a certain point where doing SEO is time consuming and takes a business person away from the tasks that are directly related to running their business. That’s a point at which hiring an SEO consultant makes sense.
He said:
“Yeah, I don’t know if there’s a one-size-fits-all answer there because it’s a bit like asking, when should I get help for marketing, especially for a small business.
You do everything yourself. At some point, you’re like, ‘Oh, I really hate bookkeeping. I’m going to hire a bookkeeper.’ At that point where you’re like, ‘Well, I don’t appreciate doing all of this work or I don’t have time for it, but I know it has to be done.’ That’s probably the point where you say, ‘Well, okay, I will hire someone for this.’ “
SEO Should Have Measurable Results?
The next factor they discussed is the measurability of results. Over more than twenty-five years of working in SEO, one of the ways that low-quality SEOs have consistently measured their results is by the number of queries a client site is ranking for. Low-quality SEOs charge a monthly retainer and generate a report of all queries the site has ranked for in the previous months, including garbage nonsense queries.
A common metric SEOs use to gauge success is ranking positions and traffic. Those metrics are a little better, and most SEOs agree that they make sense as solid metrics.
But those metrics don’t capture the true success of SEO because those ranking positions could be for low-quality search queries that don’t result in the kind of traffic that converts to leads, sales, affiliate earnings or ad clicks.
Arguably, the most important metric any business should use to gauge the effect of what was done for SEO is how much more revenue is being generated. Keyword rankings and traffic are important metrics to measure, but the most important metric is ultimately the business goal.
Google’s John Mueller appears to agree, as he cites revenue and the business result as key measures of whether the SEO is working.
He explained:
“I think, for in SEO, it kind of makes sense when you realize there’s concrete value in working on SEO for your website, where there’s some business result that comes out of it where you can actually measurably say, ‘When I started doing SEO for my website, I made so much more money’ or whatever it is that goal is that you care about, and ‘I’m happy to invest a portion of that into hiring someone to do SEO.’
That’s one way I would look at it, where if you can measure in one way or another the effects of the SEO work, then it’s easier to say, ‘Well, I will invest this much into having someone else do that for me.’”
There is a bit of a problem with measuring the effects of SEO. The effects on sales or leads from organic SEO cannot always be directly attributed. People who are obsessed with data-driven decisions will be disappointed because it’s not always possible to directly attribute a lead from an organic search. For one thing, Google hides referral data from the search results. Unlike PPC, where you can track a lead from an ad click to the sale, you can’t do that with organic search.
So if you’re using increased sales or leads as a metric, you’ll have to be able to at least separate attributable paid search from earnings, then guesstimate the rest. Not everything can be data-driven.
Hire Someone With Experience
Another thing Mueller and Splitt recommended was to hire someone who has actual experience with SEO. There are many qualifying factors that can be added, including experience monetizing their own websites, ability to interpret HTML code (which is helpful for identifying technical reasons for ranking problems), endorsements and testimonials. A red flag, in my opinion, is hiring someone from a cold call.
John Mueller observed:
“Someone else, ideally, would be someone who has more experience doing SEO. Because, as a small business owner, you have like 500 hats to wear, and you probably can figure out a little bit about each of these things, but understanding all of the details, that’s sometimes challenging.”
Martin agreed:
“Okay. So there’s no one-size-fits-all answer for this one, but you have to find that spot for yourself whenever it makes sense. All right okay. Fair.”
Red Flag About Some SEOs
Up to this point, both Mueller and Splitt avoided cautioning about red flags to watch for when hiring an SEO. Here, they segued into the topic of what to avoid, advising caution about search marketers who guarantee results.
The reason to avoid these kinds of search marketers is that search rankings depend on a wide range of factors that are not under an SEO’s control. The most an SEO can do is align a site to best practices and promote the site. After that, there are external factors, such as competitors, that cannot be influenced. Most importantly, Google is a black box system: you can see what goes in, you can observe what comes out (the search results), but what happens in between is hidden. All search ranking factors, like external signals of trustworthiness, have an unclear influence on the search results.
Here’s what Mueller said:
“One of the things I would watch out for is, if an SEO makes any promises with regards to ranking or traffic from Search, that’s usually a red flag, because a lot of things around SEO you can’t promise ahead of time. And, if someone says, “I’m an expert. I promise you will rank first for these five words.” They can’t do that. They can’t manually go into Google’s systems and tweak the dials and change the rankings.”
Listen to Google’s Search Off The Record podcast here:
Google’s martin Splitt and John Mueller discussed how long it takes for SEO to have an effect. Google’s John Mueller explained that there are different levels of optimization and that some have a more immediate effect than other more complex changes.
Visible Changes From SEO
Some SEOs like to make blanket statements that SEO is all about links. Others boast that their SEO work can have dramatic effect in relatively little time. And it turns out that those kinds of statements really depend on the actual work that was done.
Google’s John Mueller said that a site starting out from virtually zero optimization to some basic optimization may see near immediate ranking changes in Google.
John Mueller started this part of the conversation:
“I guess another question that I sometimes hear with regards to hiring an SEO is, how long does it take for them to make visible changes?”
Martin Splitt responded:
“Yeah. How long does it take? I’m pretty sure it’s not instant. If you say it takes like a week or a couple of weeks to pick things up, is that the reasonable time horizon or is it longer?”
John answered with the really old “it depends” line which is kind of overdone. But in this case it really does depend on multiple factors related to the scale of the work being done which in turn influences how long it will take for Google to index and then recalculate rankings. He said if it’s something simple then it won’t take Google much time. But if it’s a lot of changes then it may take significantly longer.
John’s explanation:
“I think, to speak in SEO lingo, it depends. Some changes are easy to pick up quickly, like simple text changes on a page. They just have to be recrawled and reprocessed and that happens fairly quickly.
But, if you make bigger, more strategic changes on a website, then sometimes that just takes a long time.”
Next Stage Of SEO: Monitor Progress
Mueller then says that a good SEO should monitor how the changes they made are affecting the rankings. This can be a little tricky because some changes will cause an immediate ranking boost that will last for a few days and then drop. My opinion, from my experience, is that an unshakeable top ranking is generally possible if there’s strong word of mouth and other external signals that tell Google that the content is trustworthy and high quality.
Here’s what John Mueller said:
“I think that’s something where a good SEO should be able to help monitor the progress along there. So it shouldn’t be that they go off and make changes and say, ‘Okay, now you have to keep paying me for the next year until we wait what happens.’ They should be able to tell you what is happening, what the progress is, give you some input on the different things that they’re doing regularly. But it is something that is more of a longer term thing.”
Mueller doesn’t go into details about what the hypothetical SEO is “doing regularly” but in my opinion it’s always helpful to be doing basic promotion that boils down to telling people that this content is out there, measuring how people respond to it, getting feedback about it and then making changes or improvement based on those changes.
For content sites, a great way to get immediate user feedback is to enable a moderated comment section in which only comments that are approved can show up. I have received a lot of positive feedback from readers on some of my content sites from what’s in the comments. It’s also useful to make it easy for users to contact the publisher from any page of the site, whether it’s an ecommerce site or an informational blog. User feedback is absolute gold.
Mueller continued his answer:
“I think if you have a website that has never done anything with SEO, probably you’ll see a nice big jump in the beginning as you ramp up and do whatever the best practices are. At some point, it’ll kind of be slow and regular more from there on.”
Martin Splitt expressed how this part about waiting and monitoring requires patience and Mueller agreed, saying:
“I think being patient is good. But you also need someone like an SEO as a partner to give you updates along the way and say, ‘Okay, we did all of these things,’ and they can list them out and tell you exactly what they did. ‘These things are going to take a while, and I can show you when Google crawls, we can follow along to see like what is happening there. Based on that, we can give you some idea of when to expect changes.’”
Takeaways:
SEO Timelines Vary By Scale Of Change
Simple on-page edits may result in quick ranking changes.
Larger structural or strategic SEO efforts take significantly longer to be reflected in Google rankings.
SEO Results Are Not Instant
Indexing and ranking recalculations take time, even for smaller changes.
Monitoring And Feedback Are Necessary
Good SEOs track progress and explain what is happening over time.
Ongoing feedback from users can help guide further optimization.
Transparency And Communication
Effective SEOs regularly report on their actions and expected timeframes for results.
Google’s John Mueller explained that the time it takes for search optimizations to show results depends on the complexity of changes made, with simple updates being processed faster and large-scale changes requiring more time. He emphasized that good SEO isn’t just about making changes because it also involves tracking how those changes affect rankings, communicating progress clearly, and continuous work.
I suggested that user response to content is an important form of feedback because it helps site owners understand what is resonating well with users and where the site is falling short. User feedback, in my opinion, should be a part of the SEO process because Google tracks user behavior signals that indicate a site is trustworthy and relevant to users.
OpenAI has quietly added Shopify as a third-party search partner to help power their shopping search, which shows shopping-rich results. The addition of Shopify was not formally announced, but quietly tucked into OpenAI ChatGPT search documentation.
Shopify Is An OpenAI Search Partner
Aleyda Solís (LinkedIn profile) recently noticed that OpenAI had updated their Search documentation to add Shopify to the list of third party search providers.
“Ecommerce sites: I’ve found that Shopify is listed along with Bing as a ChatGPT third-party search provider! OpenAI added Shopify along with Bing as a third-party search provider in their ChatGPT Search documentation on May 15, 2025; a couple of weeks after their enhanced shopping experience was announced on April 28.”
OpenAI Is Showing Merchants From Multiple Platforms
OpenAI shopping search is returning results from a variety of platforms. For example, a search for hunting dog supplies returns sites hosted on Shopify but also Turbify (formerly Yahoo Stores)
Screenshot Showing Origin Of OpenAI Shopping Rich Results
The rich results with images were sourced from Shopify and Amazon merchants for this specific query.
At least one of the shopping results listed in the Recommended Sellers is a merchant hosted on the Turbify ecommerce platform:
Screenshot Of OpenAI Recommended Retailers With Gun Dog Supply, Hosted On Turbify Platform
OpenAI Shopping Features
OpenAI recently rolled out shopping features for ChatGPT Search. Products are listed like search results and sometimes as rich results with images and other shopping related information like review stars.
ChatGPT Search uses images and structured metadata related to prices and product description, presumably Schema structured data although it’s not explicitly stated. ChatGPT may generate product titles, descriptions, and reviews based on the data received from third-party websites and sometimes may generate summarized reviews.
Merchants are ranked according to how the merchant data is received from third-party data providers, which at this point includes Bing and Shopify.
Ecommerce stores that aren’t on Shopify can apply to have their products included in OpenAI’s shopping results. Stores that want to opt in must not be opted out of OpenAI’s web crawler, OAI-SearchBot .
The old rules no longer apply. It’s time for a smarter, AI-ready playbook.
AI-driven search is changing the landscape fast. Organic traffic is dropping, visibility is shrinking, and traditional SEO tactics are losing their edge. If you’re still following yesterday’s strategy, you’re already behind.
Join Siteimproveon July 23, 2025 for an exclusive webinar with Zoe Hawkins and Jeff Coyle. Learn how to evolve your SEO approach and content planning to thrive in a world where AI now plays a central role in search.
Here’s what you’ll walk away with:
A breakdown of how AI is changing enterprise SEO.
Why trust and authority now matter more than keyword volume.
How to adapt to high-intent, low-volume traffic behavior.
We can no longer rely on the same tactics that worked before. This session gives you an inside look at how SEO must evolve to stay effective in the AI-first future.
Register now to stay ahead of the curve. Can’t attend live? Sign up anyway and get the full replay delivered to your inbox.
If you’ve been affected by AI Overviews, traffic drops, or feel uncertain about SEO’s future, then this episode is for you.
Search Engine Journal’s Editor-in-Chief Katie Morton sits down with growth advisor and author of “Growth Memo,” Kevin Indig, to unpack the results of his latest AI Overviews study.
In this 35-minute episode, they discuss how it impacts search, SEO, and brand marketing in 2025.
Editor’s note: The following transcript has been edited lightly for clarity, brevity, and adherence to our editorial guidelines.
What AI Overviews Mean For Search, SEO & Brand Trust
Katie Morton: Hi, everybody. It is I, Katie Morton. I’m the editor-in-chief of Search Engine Journal, and today I’m sitting down with Kevin Indig, who is a growth advisor to fast-growing tech companies and the author of “Growth Memo,” a fantastic newsletter.
We syndicate it here on Search Engine Journal, but sign up for it directly, too, because he has content exclusive to subscribers. It’s filled with smart insights every marketer needs to know.
Kevin, thanks for making the time today. The study was analyzed in March-April 2025 and published in May. We’ve had time to reflect, and today we’ll unpack the key takeaways.
We’ll start with the nuts and bolts of the study’s background, so listeners understand the context, and then go beyond the data to explore how marketers and companies, especially those frustrated by Google, AI Overviews, or traffic drops, can respond.
So, Kevin, can you summarize the study and share the main takeaways?
Kevin Indig: Thanks for having me on, Katie. It’s great to be here with you.
What The AI Overview Study Really Reveals
Kevin: The study came from a desire to deeply understand, from a qualitative perspective, how everyday users interact with AI Overviews.
In 2024, everyone was eyeing AI Overviews with curiosity, but traffic impact wasn’t significant yet. Then, at the start of 2025, everything changed. It became a “holy cow” moment – this was real and serious.
We asked 70 participants in the U.S., across different age groups, to solve eight tasks that covered dominant user intents: Finding a tax accountant, researching medical questions, shopping, etc.
We intentionally included queries that showed AI Overviews but didn’t tell participants to interact with them – we wanted unbiased behavior.
So, in a nutshell, the three most poignant results are:
1. Classic Organic Results Still Carry Weight
First of all – and this is no surprise – clicks are really rare when people see AI Overviews. That’s gotten through to everyone by now.
And yet, at the same time, classic organic results still have the majority of impact on people’s completion of user journeys.
Let me untangle that for a second: What we found is that people get their final answer – the final piece of information they were set out to get – 80% of the time from classic organic results. Not from AI Overviews, so that was encouraging.
2. High-Quality Clicks Happen In High-Trust Moments
Clicks are going down, but people still click. And each of those clicks has much, much higher quality than, say, in 2024 or before.
Because those clicks are to verify whether the results are accurate, to get human input from platforms like Reddit or YouTube, and to increase confidence in whether what the AI is saying is true.
And for us, that means it’s critical to be present in these high-trust, high-risk moments. I can unpack that a little more…
3. Audience Age Shapes AI Engagement
The third result I found very interesting is that there really is an age difference here. [Younger users] are much more receptive to AI answers. They’re much more active on Reddit and YouTube. Whereas people of a higher age will often just skip the AI answers because they don’t trust them.
You want to know who you’re talking to, who your target audience is. Ideally, what the age group is of your ICP or your target audience, and then make SEO decisions accordingly.
Why Branding Matters More Than Ever
Katie: Thank you for that. What I’d love to talk about next is branding.
I feel like big brands are a little safer with recent developments. If you already have recognition, you’re in a better spot. But if you’re a tiny brand with no recognition, you’re really behind the eight ball.
For the uninitiated or the uninformed, [you might wonder], why is that important? It’s about trust.
When someone sees your brand in an AI Overview, recognition boosts trust. If they click on an AI Overview or scroll to find organic results, they’re more likely to trust and click a name they know. A strong brand increases your chances.
Mordy uses the example of Nike, which was once ubiquitous, but has lost some relevance. Younger generations aren’t as loyal or aware of the swoosh anymore.
So, for big brands, maintaining confidence and trust is critical. For small or new brands, or brands that never had strong recognition, can they still gain traction?
Kevin: You can get traction … but it’s really challenging.
One challenge is that multiple teams need to work together: product, innovation, marketing, support, supply chain. SEO doesn’t control all these variables. It’s always been a discipline of recommendations, relying on others to act.
So, you always were relying on other teams, and that has 10x’d now with AI. Because, as you said, brand, brand perception, and sentiment are so critical to how you appear in search results or answers.
And it goes back to so many different touch points with a brand, not just the logo that people see or the advertising, but also the product that they use, retention, all that kind of stuff.
SEOs need to show other departments where issues lie, using click-through rates, brand search volume, and engagement metrics as signals. They must communicate the story and rally other teams.
But that often runs into cost concerns. Asking for a new call center to improve support has big budget implications, and quantifying ROI is tough.
So, SEOs must push beyond the Google channel and influence company strategy. It’s incredibly difficult to influence.
Katie: Absolutely. And speaking of SEO being declared “dead,” I’ve heard that every few years in my 20 years in the industry, but this is the first time I’ve felt a credible threat.
SEO will never truly die. It’s discovery, and discovery is always needed, but it’s definitely changing. It used to be the most cost-effective marketing channel. Now, ROI is less certain, and budgets are contracting.
But there’s a silver lining. A lot of low-quality, general content meant just to drive mass page views is getting weeded out.
For example, we used to rank for “What is E-E-A-T?” and get tons of unqualified traffic. With AI Overviews answering those general queries now, traffic is down, but the remaining traffic is far more qualified. That’s better for conversions.
It’s hard for publishers who relied on brute-force clicks. But for us, shifting away from programmatic and toward advertisers aligned with our audience, like SaaS, has worked. The industry is changing massively.
So, what do you think is next for SEO and marketing?
The New Role Of SEO In A Changing Landscape
Kevin: You hit it on the head. SEO is contracting; budgets are down, leadership confidence is down, and when people leave, their roles often aren’t replaced. SEO has died and reinvented itself many times.
I see that we’re using a lot of SEO also for AI visibility optimization. I do expect that to change, but however you flip it, we are in a transition period. And the problem with transition periods is that they’re hard to navigate. You lose orientation, and it’s painful.
Once you settle at a new baseline, you just run around a little headless, and you try to find your way. And then slowly, things kind of start to settle back in.
And so I’m very confident that whatever we’re going to call this, we’re going to settle into a new baseline. It might take a while. This is not going to stop in the next six months – probably not twelve months. But it’s hard to predict when.
Based on how quickly models improve and how quickly humans adapt to them, that will decide the pace of this transition.
However, there are also many opportunities in transitions. You can reinvent yourself. And that’s where, as SEOs, we might lose the SEO budget, but maybe we gain some brand budget, which has been much, much bigger in the past.
You see companies spending millions of dollars for multi-year contracts for a tiny logo that sits somewhere on a Formula 1 car. These things happen all the time.
There’s a big opportunity for SEO to detach from that unwanted profiling as a performance channel – detach ourselves from being a performance channel, and become much more of a brand channel, influence channel, presence channel – whatever you want to call it.
New metrics. New levers. Deeply rooted in SEO. And effective and powerful, but kind of in a new design, right? Like SEO 2.0. Whatever you want to call it.
And I do agree with you. I also see people who’ve been in the game for a long time stepping out. Totally get that. I see young people losing a bit of confidence.
But I will also say that I would like (but wouldn’t admit) that there’s a little part of me that’s kind of excited for all this change.
Because it’s an opportunity to kind of reshuffle the cards, find out new stuff, maybe find some secrets, and kind of reverse engineer what’s going on.
When you look at the last just 10 days where multiple people and companies found new ways to reverse engineer what queries Gemini uses and ChatGPT uses, I’m like, man, it’s awesome to see how adamant the industry works on developing the new playbook, dissecting how these mechanics work and LLMs work, and finding new ways.
So, I have high confidence, and I also have a lot of empathy for all the pain and the kind of problems that this industry is going through. But again, I see us coming out the other side at some point in like a new design – and with a lot of impact.
Katie Morton: I love it. I agree with the empathy as well. Because everyone in marketing, it seems, has lost their mind a little bit over the past year or two with these shifts in traffic.
But that Wild Wild West environment is also really exciting because there are going to be all of these developments.
And if people are calm and they persevere and they do the work to figure these things out, either for themselves or to watch what those researchers are finding, people will be okay, right?
Kevin: We always are. Sorry to cut you off there, but there’s a really important point to make here that I didn’t make – and that is: It’s not just search that’s changing.
SEO is at the forefront of AI. At the absolute forefront. Because it’s about words, and it’s about search, and search is kind of the biggest interface between AI and humans right now.
So it’s not just search that’s changing. Marketing is completely changing. And like, all of our lives are completely changing.
Sure, this will take years to trickle through, maybe not even to the degree we’ve thought of it, but it’s pretty clear that AI is at least as revolutionary as the internet. Maybe even the most revolutionary invention that humanity has made so far.
So let’s not forget: Everything is changing. It’s not just us SEOs. It’s all the channels. It’s marketing as a whole.
Modes and levers are disappearing, and new ones are coming up. We’re feeling it deeply in SEO, as being kind of the front line of AI. But make no mistake, this will trickle through to all the paid channels, product, everything.
Everybody is in a state of shock right now, trying to figure out what the new branches are to hold on to and then build on top of. Marketing as we know it is over. LLMs are transforming how they reach us.
Katie: This affects every channel. At SEJ, we’ve collapsed editorial and marketing into one integrated team. It used to be SEO and editorial here, marketing over there, and no one really talked. That doesn’t work anymore.
Now, everything is more cohesive and focused on the ICP and conversion. It’s better for customers and for teams.
Kevin: 100%. I talk to all my clients about this. SEO and paid search should’ve always been connected, but they were siloed, same with product, email, social, etc.
I mean, look: Realistically and ideally, SEO and paid (or paid search) have always been connected at the hip. But I’ll tell you, at least across almost all the companies that I’ve worked with, they were siloed.
The same exists with all these other teams, like product marketing or social media, conversion, and email – all that kind of stuff.
Now’s the time to rip off the band-aid. There can be small teams of maybe an SEO, an editor, an email person, a social person, and maybe a very technical person who can quickly prototype new apps, programs, or tools.
The biggest challenge now is internal red tape. AI is a speed catalyst, but companies’ old workflows slow them down. Big organizations are stuck.
I’m urging clients to form these multi-disciplinary units under one manager, one roof, one mission.
Reaching People Everywhere Requires A Bold Shift To Other Platforms
Katie: Awesome. One last point: other platforms. For too long, people relied too heavily on Google. Diversifying traffic sources – ads, social, newsletters – is now essential. Holistic marketing is the future. What are you seeing [that is] working right now?
Generally speaking, where do people live these days? Where are humans hanging out, and where do we find them? What are the success metrics that you’re seeing?
Kevin: The short answer is: Everywhere.
Katie: Good luck, everyone. Okay, good night. That’s the show!
Kevin: No, but the reality is, everywhere. There’s this interesting paradox. I need to coin this term somehow, but this interesting paradox that basically all the social networks are growing. And new ones are popping up, right? TikTok – I mean, it’s not that new anymore, but it’s still growing. Reddit is becoming much more of a household name now.
And so you ask yourself, what gives? Sure, linear TV’s down, okay. But how is this possible? And the reality is: People are online all the time – speaking for a friend – and they use a lot of platforms at the same time.
So, the best teams, or the companies that are making a big impact, they have this surround sound effect that they’re creating, where they’re present in a lot of places. They engage authentically, say, on Reddit.
When good companies engage on Reddit, it doesn’t feel like marketing. It’s not marketing, really. It’s much more like trying to be helpful, more like customer support or success.
That’s why these people are generally very well-suited to interact on Reddit. They truly add value. They’re truly part of the conversation.
Brands are repurposing their content in a very thoughtful and high-fidelity way, where maybe they create a blog article, turn it into a video, turn it into clips, which then turn into questions they answer on Reddit. There is this kind of everywhere strategy. AI really helps with that.
And I will also say it’s typically not companies that are getting stuck at the quantification-of-impact question. The reality is that steering an organization or a company toward that multi-channel effect – or that surround sound effect – takes a swing.
It takes a leader to say, “Okay, we’re going to spend some money and take six months, and we’re going to invest in Reddit and YouTube, and we’re going to wait for the results to come in. We’re not going to sit there every day refreshing the dashboard asking, ‘How many sales have we generated yet?’”
It takes a bit of a swing. And so it’s defining for this era, for this transition period, where it’s much harder to project and forecast where you’re going to land with some of these things.
It takes judgment and taste and a certain degree of risk-taking to invest in these channels and functions, and being comfortable, or at least okay, with waiting for some of the results to come in and being able to measure them later.
I’m not saying you should wait a year or two. But give it two quarters, maybe three quarters, and experiment with some of these channels.
So, that’s where people are – people are everywhere. It’s not enough to just have one shot at one platform. You need to be kind of everywhere.
And repurposing can help. Using AI with some of these things helps. But at the end of the day, you need to take a swing.
Katie: Very wise, Kevin. One of those things that I found highly annoying is that you can run these experiments, and you’re going to wait for your results, and then before your experiment is even done, everything’s changed again.
Kevin: Exactly. Predictable methods are gone. You take swings, and some won’t connect because conditions change. The best leaders, the best teams – a lot of times, they take a lot of swings.
Because some of those swings will hit full force, and it’s kind of a skill to build.
Katie: Yeah, I couldn’t agree more. We’ve implemented monthly experiments at SEJ. Every department runs one. It could be layout, content type … constant iteration. I tell the team: soft knees. Be ready to shift. There’s no “set it and forget it” anymore.
Kevin: Yes, yes. On point. Allow people to fail. Another good skill is being able to take meaningful risks. I’m not saying bet the farm, but as a leader, if you want to encourage your people to take risks, let them.
Again, that doesn’t mean to blindly shoot in all directions. You want to have some thought behind that, some judgment. You want to be critical. But there has to be a point at which you let go.
Katie: That is a really perfect point. We tie experiments to north-star metrics. For us, one is newsletter subscriptions, so most of our experiments support that. We’ve seen great success, not always in raw traffic, but in conversions and revenue.
Kevin: Amazing. Congratulations on that.
Katie: Thank you. All right, Kevin, any parting remarks before we head out?
Kevin: I’m hearing a lot of very concerned SEOs. Concerned about “How do I tell this story?” or “How do I manage my boss or leadership in this time where traffic is down?”
I want to send out some courage. This is one of the biggest shifts I’ve lived through in my life. I would bet it’s probably the same for most, if not all, of the audience.
So, this is maybe the time to make some changes and have some grace about finding a new playbook.
I’m seeing a lot of SEOs very scared about this. I get the initial fear. But again, this is such a substantial, fundamental change. It’s okay for things to look different. It’s okay for you not to have the answer right now. Be honest with leadership. Push back if needed.
Katie: Focus on new metrics, not just UVs or PVs, but ones that connect to business goals. That’s where the story of success will be told.
Kevin: Exactly.
Katie: Thanks again, Kevin. Where can people find you?
Kevin:growthmemo.com, or just search for “Growth Memo.” That’s my main hub.
Katie: Awesome. We’re at searchenginejournal.com. See you next time!
Kevin: Thanks for having me.
More Resources:
Featured Image: Paulo Bobita/Search Engine Journal
The average SEO strategy begins and ends with keyword research, with keyword volume as the deciding factor in what topics will be written about. It’s an outdated approach that fails to resonate with users and no longer reflects how modern search engines evaluate content. Content that delivers a meaningful experience across the factors that matter most to users earns trust, signals quality, and attracts links, shares, and higher rankings.
User Behavior Has Always Been A Part Of Search Ranking
User signals play a central role in Google’s ranking algorithms and the recent antitrust lawsuit against Google revealed how important these are.
One of the exhibits in the recent DOJ antitrust trial against Google featured a confidential presentation called Ranking For Research where Google noted that user behavior signals are noisy and that it takes a lot of data in order to see the patterns.
“The association between observed user behavior and search result quality is tenuous. We need lots of traffic to draw conclusions, and individual examples are difficult to interpret.”
Another Google document stated that user interaction signals are important to search rankings (PDF):
“…not one system, but a great many within ranking are built on logs. This isn’t just traditional systems, like the one I showed you earlier, but also the most cutting-edge machine learning systems, many of which we’ve announced externally– RankBrain, RankEmbed, and DeepRank.”
Google has used many kinds of user behavior signals for ranking purposes:
The Google Navboost patent ranks pages based on user interaction signals.
Google’s Trust Rank patent describes an algorithm that relies on user trust signals to identify trustworthy sites and then identifies sites that are linked from those user-trusted websites.
Google’s Branded Search patent describes an algorithm that uses navigational queries as implied links for ranking purposes.
PageRank is commonly thought of as just a link algorithm but it’s actually a way to leverage user signals in the form of the links they publish on websites. It’s also a model of user behavior because the linked nature of the web can be used to indicate which sites a user is likely to visit.
“PageRank can be thought of as a model of user behavior.”
Do Keywords Matter Anymore?
Yes, keyword still matter. But it’s been a long time since exact match keywords were a major factor that determined which sites are ranked. Look at virtually any search result and you’ll see that many top ranked sites do not contain an exact match for the keywords in a search query.
Content strategies that rely on keyword-based hubs or silos should be given a second look. Those kinds of strategies originated in the earliest days of search engines when adding exact match keywords into titles and headings was a sure way to be ranked. That’s no longer the case, so why are SEOs still stuck with keyword-based strategies that map keywords to a hub and spoke content strategy.
Logical site structure is a part of a quality user interface and makes it easy to find content. Focus on that and interlink in ways that make sense to users.
Try thinking in terms of topics that users are interested in and see how far that takes you.
Write With The Purpose To Be Understood
I’m going to share an advanced concept about writing that helps sentences, paragraphs and entire web pages reach an audience more effectively.
Cognitive Load
There is a scientific concept called cognitive load. In the context of reading, cognitive load is the amount of mental effort used to process information.
For example, sentences with confusing instructions or jargon can take extra effort to process. When the load exceeds a certain threshold, the person’s ability to understand or learn from what they’re reading suffers.
Cognitive Dissonance
I have my own theory that’s similar to cognitive load that I call cognitive dissonance. It’s not something scientific that I read, it’s just my own theory.
Dissonance means a lack of harmony, when sounds clash. Poor writing can be dissonant due to the choice of words that are abstract (lack a clear meaning or have multiple meanings) , using jargon, or simply using words that aren’t commonly understood.
Another source of dissonance is writing a paragraph that rambles rather than builds up to an idea.
Cognitive dissonance causes a reader to lose track of what they’re reading and consequently engage less with the content.
Here’s the same sequence of paragraphs you just read, with an explanation of their purpose:
1. Define the idea: I explain that I have a personal theory
I have my own theory that’s similar to cognitive load that I call cognitive dissonance. It’s not something scientific that I read, it’s just my own theory.
2. Explain my idea with a definition and metaphors
Dissonance means a lack of harmony, when sounds clash…
3. Apply the metaphor to writing:
Poor writing can be dissonant due to the choice of words…
4. Expand the definition to paragraph structure
Another source of dissonance is writing a paragraph that rambles rather than builds up to an idea.
5. The big idea I was building up to: What it all means
Cognitive dissonance causes a reader to lose track of what they’re reading and consequently engage less with the content.
SEOs like to talk about hooks and other little tricks to writing, but good writing is not about tricking the user. It’s about clear communication. It doesn’t always come out right the first time the words spill onto the page. Sometimes it helps to step away and come back to it for the errors in sentence and paragraph structure to become visible.
Crafting Content Around the User Experience
Publishers who build sites around keywords face an uphill struggle obtaining links, and since links remain an important ranking factor, it makes sense that the SEO strategy works together with obtaining links. This is where user experience marketing shines.
Nobody links to a keyword-based site because the keywords make them feel good about the site. Keyword-based sites feel sterile because they are optimized for keywords, not people. That approach also results in a made-for-search-engine website structure. Nothing screams “made for search engines” like sitewide title tags with keywords ripped from Google’s People Also Asked keyword lists.
What I would suggest is to acquaint yourself with who you’re writing for by speaking to people who are interested in your topic, joining some Facebook groups, checking out popular forums, listening to podcasts about the topic, watching YouTube videos about your topic, and reading the comment sections of those videos. This will not only give you an idea of what people are talking about, it will show you how they’re talking about it and quite possibly give you ideas for your business, whether that’s selling things online or writing about a topic
Users Share Experiences, Not Links
Perhaps the best kind of link is the kind created because of a positive experience (learning, usefulness, fun). Scientific research has discovered that experiences motivate sharing and that positive experiences are shared the most.
Insight: Those aren’t just links that people are sharing. Links from one website to another website or even on social media, are the expression of the experiences people had with a website. Cultivate positive experiences and people will begin linking and sharing your website.
Insight: Devoting time to the user experience is a pragmatic approach to promoting a website because inspiring site visitors with emotional resonance, a feeling, is a sure way to encourage more sales, more links, and more traffic. And that’s why we optimize, right? To make more money.
Make Visitors Want To Return
Make your content (even if they’re products) easily viewable from the top of the fold
Make your content easy to scan (with headings)
Offer related articles at key points where visitors tend to become disinterested
Encourage messaging opt-ins
Post-Transaction Experience
Successful entrepreneur Justin Sanger pointed out that everyone knows about the sales funnel, but less well known is the funnel that opens up after the sale. He calls this upside-down funnel the Post-Transaction Funnel. The Post-Transaction Funnel represents all the things you can do to send a signal back to the search engines that site visitors had a good experience at your website. This activity includes:
Encouraging social sharing
Cultivating good reviews
Encouraging word of mouth referrals
Cultivating relationships with non-competitors in your space
I believe it is a good practice to consider the post-transaction funnel because those are the kinds of activities that tend to cultivate more sales. Post-transaction marketing is something to consider outside of the Classic SEO box.
1. User-behavior signals are used within Google’s various algorithms and machine learning systems as evidence of page quality and trust.
2. Logically considered, visitor-friendly sentence, paragraph, page, and site architecture that makes it easy to understand information supports strong quality signals.
3. Content that uses clear, jargon-free sentences and paragraphs that build logically enables readers to process information effortlessly and helps build a better user experience.
4. Content planned around user experience rather than exact-match keywords makes pages feel more human-centered and less like they were made for search engines, which contributes to greater trust.
5. Positive emotional experiences that motivate natural sharing and backlinks act as strong indicators of authority and trust.
6. Page design that includes above-the-fold visibility, scannable headings, related-article prompts, and opt-ins helps keep visitors engaged, active, and returning, reinforcing external content quality signals.
7. Post-transaction funnel actions, such as encouraging reviews, social sharing, and word-of-mouth referrals, feed satisfaction signals back to search engines and strengthen trustworthiness.
It is important to recognize that the foundation of a successful website is the user experience. Even a successful PPC landing page is crafted with the principle of a quality end-to-end user experience, from the layout and ease of data delivery to convenience.
User experience marketing is about moving beyond simple keyword phrase optimization, with a content strategy built on understanding what that content means to the user. Is it important? Is it entertaining? Does it rock, and does it roll?
Relevance is still king, but the definition of relevance is now focused on the user, not your keywords.
For years, businesses published blogs to attract traffic, any traffic. An online appliance store, for example, might publish an article unrelated to appliances so long as it attracts visitors to the site.
But irrelevant content in circa 2025 likely hurts organic search visibility and confuses large language models.
Here’s how search and AI algorithms treat content relevance.
Organic Search
Google once assigned relevance signals on a page level. A page could rank well and drive traffic even if its content was irrelevant to the site.
Prominent sites started experiencing traffic losses. Take HubSpot, for example. In April 2022, HubSpot ranked for search queries unrelated to its core marketing platform, such as “personality test” and “real estate license.” Then it lost roughly 80% of its organic traffic, per Semrush.
HubSpot subsequently deleted all unrelated pages, resulting in much less traffic but higher overall revenue, presumably owing to attracting qualified prospects, not mere visitors.
According to Semrush, HubSpot has maintained top rankings for relevant queries, such as “conversion rate optimization” and “brand strategy.”
In early 2024, Google announced an algorithm update for site reputation abuse, which Google defined as “when third-party pages are published with little or no first-party [editorial] oversight or involvement, where the purpose is to manipulate Search rankings by taking advantage of the first-party site’s ranking signals.”
Site reputation abuse was another signal that irrelevant content could damage overall site rankings. Google even reportedly deindexed entire sections of various offending business publications.
Large Language Models
We’re all learning how to optimize for mentions and citations in ChatGPT, Claude, Gemini, AI Overviews, and more. Publishing irrelevant content likely confuses those models.
LLMs focus on a site’s context and expertise to determine whether to mention or cite it. Irrelevant content can dilute the context and confuse AI algorithms, lowering the chances of the site appearing in AI-driven answers.
In short, irrelevant content that doesn’t address your business niche and value proposition may hurt your online visibility in AI as well as Google.
Unless you are in a publishing business, consider removing irrelevant content. Unfortunately, “relevance” is vague. Content doesn’t have to describe your products directly. It could address the problems of your target audience and still be helpful and relevant.
Here’s a table for managing irrelevant content.
Action
Content Type
Tips
Delete content and let links go to a 404 page.
Any content that becomes irrelevant to the business.
Remove all internal links to these pages; confirm with Screaming Frog or a similar crawler.
Leave content published, but redirect inbound links; block crawlers in robots.txt file.
Old instructions or tutorials on using discontinued products or outdated features. Users of old products will still use this content.
Block all crawlers, including AI crawlers. Block only an archive folder or equivalent, not the entire site.
Noindex the URLs.
Any irrelevant content. Some sites prefer noindexing because it avoids broken URLs or creating new folders. However, in most cases, it’s the weakest choice because noindexing is not supported by many AI platforms, and it won’t stop any bots from crawling old URLs, resulting in unnecessary server load and page speed hits.
Noindexing blocks irrelevant content from ranking in Google (and being penalized from site reputation abuse), but I do not recommend it in most cases.