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Think AI can fully run your marketing strategy on autopilot?
Or that AI-generated content should deliver instant results?
It is time to bust the AI myths that are slowing you down and costing you money.
Join Bailey Beckham, Senior Partner Marketing Manager at CallRail, and Jennifer McDonald, Senior Marketing Manager at Search Engine Journal, on August 21, 2025, for an exclusive webinar. Get the insights you need to stop wasting time and money and start leveraging AI the right way.
In this session, you will learn:
Why this session is essential:
AI tools can’t run your strategy on autopilot. You need to make smarter decisions, ask the right questions, and guide your AI tools to work for you, not against you.
This webinar will help you unlock AI’s full potential and optimize your content to improve your marketing performance.
Register now to learn how to get your content loved by AI, LLMs, and most importantly, your audience. Can’t attend live? Don’t worry, sign up anyway, and we will send you the on-demand recording.
AI is rapidly changing the rules of SEO. From generative ranking to vector search, the new rules are not only technical but also reshaping how business leaders make decisions.
Join Dan Taylor on August 14, 2025, for an exclusive SEJ Webinar tailored for C-suite executives and senior leaders. In this session, you’ll gain essential insights to understand and communicate SEO performance in the age of AI.
Here’s what you’ll learn:
AI Search Is Impacting Everything. Are You Ready?
AI search is already here, and it’s impacting everything from SEO KPIs to customer journeys. This webinar will give you the tools to lead your teams through the shift with confidence and precision.
Register now for a business-first perspective on AI search innovation. If you can’t attend live, don’t worry. Sign up anyway, and we’ll send you the full recording.
A few weeks ago, I fell down a rabbit hole of cottagecore TikTok and Japanese jazz-funk from the ’70s. I didn’t search for it. I didn’t ask for it. But, somehow, my For You Page and Spotify knew. They knew before I did.
That’s the power of what I call B2Me, from broad strokes to a segment of one. And it’s changing everything.
As marketers, we’re moving from static personas to living identity graphs. As audiences, we’ve gone from craving options to craving intuition. We want brands that just get us.
Picture ads that shift based on your inferred mood, product recommendations that feel like they were plucked straight from your subconscious, content around what you were only just thinking about.
We’re marketing to real people in real time. And the brands that get it right, get rewarded with clicks, loyalty, and trust.
Demographics Were Always Broken (AI Just Made It Obvious)
For decades, we, marketers, clung to personas. Those convenient, yet ultimately flawed, cardboard cutouts like “Marketing Mike,” who supposedly loved artisanal everything, skateboarded to work, and breakfasted on avocado toast.
Meanwhile, the real Mike was out buying a motorcycle, years past his skateboarding phase, and loves gas station hotdogs.
“Women aged 25-34 with college degrees who live in New York and work in marketing” tells you nothing about what Natasha actually wants, what she’s struggling with, or what would make her say yes.
For too long, we’ve marketed to people who look like our customers instead of those who act like them.
Even today, many companies claiming “personalized marketing” are still relying on a demographic infrastructure from 2019, if not earlier. It’s a bit like driving forward while looking in the rearview mirror.
Demographics were always stereotypes in a data suit. AI strips that away and sees the person underneath.
That’s the essence of B2Me marketing: connecting with individuals based on observed behavior, not assumed demographics.
Decisions happen in fleeting, emotional moments. AI recognizes intent in real time, often before we do.
When was the last time an algorithm recommended something you didn’t know you wanted, but it was exactly what you wanted? Creepy? Maybe. Useful? Yes.
That’s the emotional layer AI is tapping into. It’s going beyond tracking behavior to interpreting intent. Frustration. Curiosity. Readiness. These are signals. And our job as marketers is to listen when they’re telling us, often without saying a word.
What True B2Me Looks Like
Coca-Cola tested this in Saudi Arabia. Instead of targeting “Millennials,” its AI agent analyzed millions of social posts across platforms like TikTok and LinkedIn, identifying people expressing cravings for fast food.
It then delivered 828,000 personalized coupon ads for discounted Coke products – 20,000 of which were clicked on – all without human intervention.
Overall, it executed roughly 8 million autonomous actions on behalf of its marketing team. That’s behavioral precision at unprecedented scale.
Meanwhile, a project management software company I observed found that its highest-converting customers weren’t the enterprise IT directors its demographic models targeted.
It was mid-level operations managers, the ones actually wrestling with the workflows. They weren’t filling out forms. But, they were driving the deals. The invisible layer of influence was profound.
B2Me strategies create compounding advantages. Each interaction refines AI’s understanding of individual patterns, leading to more precise future targeting. This can translate to:
Faster, more accurate intent recognition.
Superior message-market fit.
Measurably higher conversion rates.
Enhanced customer lifetime value.
Why Most “B2Me” Efforts Fail
Because they’re not really B2Me. They’re just demographic micro-segmentation with fancier plumbing.
I watched a SaaS company spend six months building an “AI-powered individual targeting system.” Its big breakthrough? Sending different subject lines to “Marketing Managers” versus “Marketing Directors.”
That’s not B2Me. That’s lipstick on a persona.
True B2Me watches behavior. It asks: What are they doing? What are they feeling? What are they trying to solve? And it zeroes in on the behavioral patterns that predict buying intent.
B2Me thrives on living identity graphs that continuously evolve based on what individuals consume, click, purchase, and how they navigate content.
Salesforce, through its focus on comprehensive customer data within frameworks like Customer 360, enables businesses to leverage behavioral signals, such as rapid tool adoption or shifts in company structure, to identify opportunities for digital transformation and improve targeting effectiveness.
These “digital transformation stress signals” convert significantly higher than demographic targeting, regardless of company size.
3 Ways To Implement B2Me
1. Target Behavior, Not Job Titles
Traditional: “Target CISOs at Fortune 500 companies.”
Job titles aren’t always accurate predictors of buying behavior. Your best prospects might not match your ideal customer profile (ICP) on paper, but they’re showing you who they are through their actions.
2. Time Messages To Emotional States
AI’s true power lies in its ability to detect human intent and emotional states.
It can sense things like frustration (rapid scrolling, quick exits), curiosity (deep engagement, repeated visits), and buying readiness (pricing page visits, competitor research). This goes beyond what someone does to how they do it.
HubSpot’s platform and integrations support outreach timing based on behavioral frustration signals such as prospects engaging with content about data migration headaches or sales team bottlenecks.
3. Predict Needs Before Searches
Zoom capitalized on early remote work signals, such as increased interest in collaboration tools, distributed team hiring, and work-from-home content consumption, to scale rapidly during the pandemic
It identified “remote work scaling signals,” i.e., companies actively researching collaboration tools, posting jobs for distributed teams, and consuming work-from-home content.
This foresight allowed it to engage prospects and capture demand before competitors even fully recognized the shift.
Getting Started
1. Map Real Customer Behavior
Begin by auditing your current targeting. Most companies, from my observation, are still operating at 80% demographics, 20% behavior. It’s time to work on inverting that ratio.
Document what your actual best customers do before they buy:
What content truly resonates?
What questions consistently emerge during sales conversations?
What research triggers precede their engagement?
What are their preferred engagement channels?
2. Build Behavioral Audiences
Build behavioral audiences using the tools you already have in your search and social platforms.
These platforms are already prioritizing behavioral signals over static demographics, so lean into their capabilities.
Brand Still Wins
AI can distill patterns, but it can’t feel. It segments behavior, but it doesn’t grasp human motivation. It predicts clicks, but it can’t forge connection.
This is where brand is essential. It can serve as a definitive advantage in AI-mediated decisions.
When someone asks an AI assistant for customer relationship management (CRM) recommendations, which brands show up? And more importantly, how are they described?
You’re not just competing for human memory anymore. You’re competing for AI memory. And your brand is the shortcut.
When an AI recommends brands, it’s synthesizing reputation and consistency across thousands of complex touchpoints.
We can’t talk about brand without talking about trust.
We’ve always said “trust matters.” Now, AI exposes what trust really is: the gap between what you can do and what you should do.
Remember that Coca-Cola campaign? Eight million social posts analyzed, 828,000 personalized coupons delivered autonomously. Impressive results … and also a few debates about “surveillance marketing.”
AI exposes where trust was always fragile. Take surge pricing. AI can adjust rates based on your browser history, your device, even your cursor hesitation.
But, when customers notice? “Smart” becomes “sneaky.” Trust evaporates. Remember, trust isn’t a feature you add later. It’s the foundation.
The Right People At The Right Time With The Right Message
B2Me is about fundamentally better understanding your customer. AI can help us see patterns. But, only we can make meaning. Only we can build trust. Only we can decide what matters.
B2Me is empathy at scale, helping you see people, not personas. It empowers you to show up in the moments that matter, even the ones we’ll never see.
B2Me bridges the gap between what’s technically possible and what’s strategically smart.
You don’t need to have it all figured out tomorrow. You just need to start. And start by remembering that the most powerful force in marketing is still a thinking human.
More Resources:
Featured Image: Paulo Bobita/Search Engine Journal
This post was sponsored by Peec.ai. The opinions expressed in this article are the sponsor’s own.
The first step of any good GEO campaign is creating something that LLM-driven answer machines actually want to link out to or reference.
GEO Strategy Components
Think of experiences you wouldn’t reasonably expect to find directly in ChatGPT or similar systems:
Engaging content like a 3D tour of the Louvre or a virtual reality concert.
Live data like prices, flight delays, available hotel rooms, etc. While LLMs can integrate this data via APIs, I see the opportunity to capture some of this traffic for the time being.
Topics that require EEAT (experience, expertise, authoritativeness, trustworthiness).
LLMs cannot have first-hand experience. But users want it. LLMs are incentivized to reference sources that provide first-hand experience. That’s just one of the things to keep in mind, but what else?
We need to differentiate between two approaches: influencing foundational models versus influencing LLM answers through grounding. The first is largely out of reach for most creators, while the second offers real opportunities.
Influencing Foundational Models
Foundational models are trained on fixed datasets and can’t learn new information after training. For current models like GPT-4, it is too late – they’ve already been trained.
But this matters for the future: imagine a smart fridge stuck with o4-mini from 2025 that might – hypothetically – favor Coke over Pepsi. That bias could influence purchasing decisions for years!
Optimizing For RAG/Grounding
When LLMs can’t answer from their training data alone, they use retrieval augmented generation (RAG) – pulling in current information to help generate answers. AI Overviews and ChatGPT’s web search work this way.
As SEO professionals, we want three things:
Our content gets selected as a source.
Our content gets quoted most within those sources.
Other selected sources support our desired outcome.
Concrete Steps To Succeed With GEO
Don’t worry, it doesn’t take rocket science to optimize your content and brand mentions for LLMs. Actually, plenty of traditional SEO methods still apply, with a few new SEO tactics you can incorporate into your workflow.
Step 1: Be Crawlable
Sounds simple but it is actually an important first step. If you aim for maximum visibility in LLMs, you need to allow them to crawl your website. There are many different LLM crawlers from OpenAI, Anthropic & Co.
Some of them behave so badly that they can trigger scraping and DDoS preventions. If you are automatically blocking aggressive bots, check in with your IT team and find a way to not block LLMs you care about.
If you use a CDN, like Fastly or Cloudflare, make sure LLM crawlers are not blocked by default settings.
Step 2: Continue Gaining Traditional Rankings
The most important GEO tactic is as simple as it sounds. Do traditional SEO. Rank well in Google (for Gemini and AI Overviews), Bing (for ChatGPT and Copilot), Brave (for Claude), and Baidu (for DeepSeek).
Step 3: Target the Query Fanout
The current generation of LLMs actually does a little more than simple RAG. They generate multiple queries. This is called query fanout.
For example, when I recently asked ChatGPT “What is the latest Google patent discussed by SEOs?”, it performed two web searches for “latest Google patent discussed by SEOs patent 2025 SEO forum” and “latest Google patent SEOs 2025 discussed”.
Advice: Check the typical query fanouts for your prompts and try to rank for those keywords as well.
Typical fanout-patterns I see in ChatGPT are appending the term “forums” when I ask what people are discussing and appending “interview” when I ask questions related to a person. The current year (2025) is often added as well.
Beware: fanout patterns differ between LLMs and can change over time. Patterns we see today may not be relevant anymore in 12 months.
Step 4: Keep Consistency Across Your Brand Mentions
This is something simple everyone should do – both as a person and an enterprise. Make sure you are consistently described online. On X, LinkedIn, your own website, Crunchbase, Github – always describe yourself the same way.
If your X and LinkedIn profiles say you are a “GEO consultant for small businesses”, don’t change it to “AIO expert” on Github and “LLMO Freelancer” in your press releases.
I have seen people achieve positive results within a few days on ChatGPT and Google AI Overviews by simply having a consistent self description across the web. This also applies to PR coverage – the more and better coverage you can obtain for your brand, the more likely LLMs are to parrot it back to users.
Step 5: Avoid JavaScript
As an SEO, I always ask for as little JavaScript usage as possible. As a GEO, I demand it!
Most LLM crawlers cannot render JavaScript. If your main content is hidden behind JavaScript, you are out.
Step 6: Embrace Social Media & UGC
Unsurprisingly, LLMs seem to rely on reddit and Wikipedia a lot. Both platforms offer user-generated-content on virtually every topic. And thanks to multiple layers of community-driven moderation, a lot of junk and spam is already filtered out.
While both can be gamed, the average reliability of their content is still far better than on the internet as a whole. Both are also regularly updated.
reddit also provides LLM labs with data into how people discuss topics online, what language they use to describe different concepts, and knowledge on obscure niche topics.
We can reasonably assume that moderated UGC found on platforms like reddit, Wikipedia, Quora, and Stackoverflow will stay relevant for LLMs.
I do not advocate spamming these platforms. However, if you can influence how you and competitors show up there, you might want to do so.
Step 7: Create For Machine-Readability & Quotability
Write content that LLMs understand and want to cite. No one has figured this one out perfectly yet, but here’s what seems to work:
Use declarative and factual language. Instead of writing “We are kinda sure this shoe is good for our customers”, write “96% of buyers have self-reported to be happy with this shoe.”
Add schema. It has been debated many times. Recently, Fabrice Canel (Principal Product Manager at Bing) confirmed that schema markup helps LLMs to understand your content.
If you want to be quoted in an already existing AI Overview, have content with similar length to what is already there. While you should not just copy the current AI Overview, having high cosine similarly helps. And for the nerds: yes, given normalization, you can of course use the dot product instead of cosine similarity.
If you use technical terms in your content, explain them. Ideally in a simple sentence.
Add summaries of long text paragraphs, lists of reviews, tables, videos, and other types of difficult-to-cite content formats.
Step 8: Optimize your Content
The original GEO paper
If we look at GEO: Generative Engine Optimization (arXiv:2311.09735) , What Evidence Do Language Models Find Convincing? (arXiv:2402.11782v1), and similar scientific studies, the answer is clear. It depends!
To be cited for some topics in some LLMs, it helps to:
Add unique words.
Have pro/cons.
Gather user reviews.
Quote experts.
Include quantitative data and name your sources.
Use easy to understand language.
Write with positive sentiment.
Add product text with low perplexity (predictable and well-structured).
Include more lists (like this one!).
However, for other combinations of topics and LLMs, these measures can be counterproductive.
Until broadly accepted best practices evolve, the only advice I can give is do what is good for users and run experiments.
Step 9: Stick to the Facts
For over a decade, algorithms have extracted knowledge from text as triples like (Subject, Predicate, Object) — e.g., (Lady Liberty, Location, New York). A text that contradicts known facts may seem untrustworthy. A text that aligns with consensus but adds unique facts is ideal for LLMs and knowledge graphs.
So stick to the established facts. And add unique information.
Step 10: Invest in Digital PR
Everything discussed here is not just true for your own website. It is also true for content on other websites. The best way to influence it? Digital PR!
The more and better coverage you can obtain for your brand, the more likely LLMs are to parrot it back to users.
I have even seen cases where advertorials were used as sources!
Concrete GEO Workflows To Try
Before I joined Peec AI, I was a customer. Here is how I used the tool – and how I advise our customers to use it.
Learn Who Your Competitors Are
Just like with traditional SEO, using a good GEO tool will often reveal unexpected competitors. Regularly look at a list of automatically identified competitors. For those who surprise you, check in which prompts they are mentioned. Then check the sources that led to their inclusion. Are you represented properly in these sources? If not, act!
Is a competitor referenced because of their PeerSpot profile but you have zero reviews there? Ask customers for a review.
Was your competitor’s CEO interviewed by a Youtuber? Try to get on that show as well. Or publish your own videos targeting similar keywords.
Is your competitor regularly featured on top 10 lists where you never make it to the top 5? Offer the publisher who created the list an affiliate deal they cannot decline. With the next content update, you’re almost guaranteed to be the new number one.
Understand the Sources
When performing search grounding, LLMs rely on sources.
Look at the top sources for a large set of relevant prompts. Ignore your own website and your competitors for a second. You might find some of these:
A community like Reddit or X. Become part of the community and join the discussion. X is your best bet to influence results on Grok.
Aninfluencer-driven website like YouTube or TikTok. Hire influencers to create videos. Make sure to instruct them to target the right keywords.
Anaffiliate publisher. Buy your way to the top with higher commissions.
Anews and mediapublisher. Buy an advertorial and/or target them with your PR efforts. In certain cases, you might want to contact their commercial content department.
Once you have observed which searches are triggered by query fanout for your most relevant prompts, create content to target them.
On your own website. With posts on Medium and LinkedIn. With press releases. Or simply by paying for article placements. If it ranks well in search engines, it has a chance to be cited by LLM-based answer engines.
Position Yourself for AI-Discoverability
Generative Engine Optimization is no longer optional – it’s the new frontline of organic growth. At Peec AI, we’re building the tools to track, influence, and win in this new ecosystem.
Generative Engine Optimization is no longer optional – it’s the new frontline of organic growth. We currently see clients growing their LLM traffic by 100% every 2 to 3 months. Sometimes with up to 20x the conversation rate of typical SEO traffic!
Whether you’re shaping AI answers, monitoring brand mentions, or pushing for source visibility, now is the time to act. The LLMs consumers will trust tomorrow are being trained today.
Too often in our content and messaging, we default to listing features in a succession of brief, disconnected claims rather than showing readers how those features will make a genuine difference in their lives.
As a result, they are left to fill in the gaps themselves, often choosing to skim and move on rather than engage with that cold list of facts.
It’s common for us to focus heavily on features, then expect our audience to understand how those features directly impact them.
Instead, by describing a scenario in which users experience the benefits of the features, you invite the user to picture themselves using the features as part of their day-to-day life. That mental rehearsal is what sparks genuine interest.
In this article, we examine how to transition from “we have X” to “you will Y” and why this shift is more crucial than ever in today’s AI-driven search landscape.
As search engines now showcase AI Overviews or AI Mode snippets that extract passages of our copy into results pages and dashboard panels, those bite-sized answers may earn clicks.
However, every sentence must stand alone, or risk having nuance stripped out.
Headlines should hint at benefits, subheads need to frame outcomes, and meta descriptions become miniature forecasts rather than mere summaries.
Because Overviews appear outside the full context of the page it’s taken from, every word must carry weight and meaning on its own.
By weaving context and emotional hooks directly into key sentences, we can direct AI tools to lift passages that still resonate and invite deeper exploration.
Image from author, July 2025
Defining Experience Forecasting
Experience forecasting is the practice of writing so vividly that readers can mentally rehearse using your product or service.
For a city break tours website, you might describe stepping off the train into Barcelona’s Gothic Quarter, following a curated walking tour that reveals hidden plazas, tantalizes with local tapas bars, and culminates in sunset views over the Mediterranean.
At the same time, for invoicing software, you could paint a picture of logging in to discover that overdue invoices have been sent automatically, payments are tracked in real time, and tax reports appear at the click of a button, allowing finance teams to close their books in minutes rather than hours.
In both cases, readers will imagine themselves in those moments of discovery and relief.
This technique relies on three complementary elements: scene setting through sensory details, emotional framing to highlight feelings such as relief and confidence, and a tangible payoff that demonstrates results like time saved or stress reduced.
Guiding Users Through Ambiguous Journeys
Because many search queries begin in a zone of uncertainty, questions such as how to plan a trip to Italy, what constitutes a healthy breakfast, or which tools best serve remote teams indicate that readers are exploring.
If your page opens with a laundry list of features, this will risk causing them to bounce.
Instead, guiding users with a vivid scenario immediately captures their attention by giving them a vision of success, such as picturing themselves strolling cobblestone streets in Rome on a custom itinerary that balances must‑see landmarks with hidden cafés.
By meeting readers at this exploratory stage, we can transform passive browsers into engaged readers who refine their own goals as they proceed.
Demonstrating that we understand their uncertainty builds trust, and previewing what success looks like shapes intent.
Forecastable Messaging In Action
We can tap into sensory memory and create an experience that sticks in the mind by describing the balcony, the sea, and the espresso.
By transforming before:
“A luxury hotel on the Amalfi Coast, with complimentary breakfast.”
To after:
“Wake up on your private balcony as the sun glints off the Tyrrhenian Sea, sip fresh Italian espresso while planning your morning adventure, and join us for a complimentary breakfast of flaky pastries and locally sourced cheeses, providing fuel for a day of discovery.”
If an AI tool then lifts a fragment of our description, such as “sipping fresh Italian espresso, while planning your morning adventure,” that phrasing still has the power to entice because it hints at both flavor and purpose.
Vivid details, such as “a private balcony overlooking the Tyrrhenian Sea” and “locally sourced cheeses,” can broaden our semantic footprint.
This helps to capture long-tail queries around experiences rather than generic hotel terms, which could ultimately increase the likelihood that readers move from casual browsing to booking.
Image from author, July 2025
Forecasting Against The Funnel
Experience forecasting can enhance every stage of the funnel by sparking curiosity and building emotional hooks at the awareness stage.
Creating broad scenarios with narrative case studies, such as “imagine your team collaborating seamlessly from anywhere,” can help to validate decisions at the consideration stage, which can improve click-through rates and time on page.
Introducing reminders of the end reward at the conversion stage can help close a deal, such as offering free cancellation up to 24 hours before arrival, alongside a claim that customers save an average of $5,000 in their first year, to increase completion rates and purchase conversions.
For example, validations, such as “When Acme Corp adopted our platform, they cut project delays by 30%,” encourage readers to imagine comparable gains.
Purpose, which means that every piece must address a clear user need, whether helping readers choose, compare, or commit, and stating that objective up front.
Showcasing expertise, by linking claims to real-world proof, such as data points, practitioner quotes, or firsthand anecdotes, and providing sources for assertions like “instant setup in five minutes.”
Originality, which involves avoiding clichés by grounding imagery in authentic capabilities and experiences that only you can deliver.
Key Questions For Content Creators
Before publishing, use a comprehensive checklist that confirms:
The problem being addressed is stated in relatable terms.
Each paragraph includes sensory or emotional details to help readers imagine the outcome.
Claims are supported by data, case studies, or user quotes.
The angle differs from competitors through fresh insights.
Section openers carry meaning when read in isolation.
Forecast tactics align with key metrics such as click-through rate, time on page, or form completions.
The narrative guides readers naturally from uncertainty to clarity and action.
Image from author, July 2025
Final Thoughts
As search engines and AI continue to evolve, our copy must do more.
Transport readers into scenarios where they feel the benefit by weaving sensory details into every line.
This helps us stand out from the homogeneous, safe content that a lot of the internet has been built on.
Back up claims with evidence and constantly ask how effectively each sentence enables readers to imagine their success.
This helps to align with neural search models, feeding inclusion in AI Overviews, which then drives meaningful business results such as clicks and conversions.
Ultimately, words become experiences; experiences become results.
As generative search becomes the default for tools like ChatGPT, Gemini, and Claude, fewer people are clicking through to traditional search results. If your content isn’t part of their training data or grounding sources, it’s effectively invisible.
And that means one thing: you’re no longer just optimizing for humans or search engines. You’re optimizing for machines that summarize the internet.
Introducing Generative Engine Optimization (GEO)
In this tactical webinar, we’ll break down what it takes to get your brand cited, linked, and quoted in AI-generated content, intentionally.
Ways to increase your AIO (AI Overview) brand presence.
Proven SEO & GEO workflows you can copy today.
Learn How To Influence LLMs
This isn’t theory. We’ll walk through the specific strategies SEOs and marketers are using right now to shape what language models say, and don’t say, about their brands.
Expect insights on:
How foundational training data is gathered (and how you might influence it).
Which formats and language structures improve your chances of being cited.
This is for SEOs, content strategists, and marketing leads who want to stay relevant as AI redefines the playing field.
Why This Webinar Is A Must-Attend
Whether you’re refining your search strategy or trying to future-proof your brand visibility, this session offers high-ROI insights you can apply immediately.
✅ Actionable examples
✅ Real-world GEO workflows
✅ Early looks at emerging standards like MCP, A2A, and llms.txt
📍 Designed for experienced marketers ready to lead change.
Reserve Your Spot Or Get The Recording
🛑 Can’t make it live? No problem. Register anyway, and we’ll send you the full recording so you don’t miss a thing.
I recently saw Stephen Kenwright speak at a small Sistrix event in Leeds about strategies for exploiting Google’s brand bias, and a lot of what he said still feels as fresh today as it did over a decade ago when he first started promoting this theory.
Some might say (Stephen included) that this is what SEO should always have been about.
I spoke to Stephen, the founder of Rise at Seven, about his talk and about how his theories and strategies could translate to a world of large language model (LLM) optimization alongside a fractured search journey.
You can watch the full interview with Stephen on IMHO below, or continue reading the article summary.
Google’s Brand Bias Is Foundational
Brand bias isn’t a recent development. Stephen was already writing about it in 2016 during his time at Branded3. What underlines this bias is the trust users have in brands.
“Google wants to give a good experience to its users. That means surfacing the results they expect to see. Often, that’s a brand they already know,” Stephen explained.
When users search, they’re often subconsciously looking to reconnect with a mental shortcut that brands provide. It’s not about discovery; it’s about recognition.
When brands invest in traditional marketing channels, they influence user behavior in ways that create cascading effects across digital platforms.
Television advertising, for example, makes viewers significantly more likely to click on branded results even when searching for generic terms.
Traditional Marketing Directly Influences Search Behavior
At his talk in Leeds, Stephen referenced research that demonstrates television advertising creates measurable impacts on search behavior, with viewers 33% more likely to click on advertised brands in search results.
“People are about a third more likely to click your result after seeing a TV ad, and they convert better, too,” Stephen said.
When users encounter brands through traditional marketing channels, they develop mental associations that influence their subsequent search behavior. These behavioral patterns then signal to Google that certain brands provide better user experiences.
“Having the trust from the user comes from brand building activity. It doesn’t come from having an exact match domain that happens to rank first for a keyword,” Stephen emphasized. “That’s just not how the real world works.”
Investment In Brand Building Gains More Buy-In From C-Suite
Even though this bias has been evident for so long, Stephen highlighted a disconnect from brand-building activities within the industry.
“Every other discipline from PR to the marketing manager through to the social media team, literally everyone else, including the C-suite is interested in brand in some capacity and historically SEOs have been the exception,” Stephen explained.
This separation has created missed opportunities for SEOs to access larger marketing budgets and gain executive support for their initiatives.
By shifting focus toward brand-building activities that impact search visibility, they can better align with broader marketing objectives.
“Just by switching that mindset and asking, ‘What’s the impact on brand of our SEO activity?’ we get more buy-in, bigger budgets, and better results,” he said.
Make A Conscious Decision About Which Search Engine To Optimize For
While Google’s dominance remains statistically intact, user behavior tells us that there has always existed a fractured search journey.
Stephen cited that half of UK adults use Bing monthly. A quarter is on Quora. Pinterest and Reddit are seeing massive engagement, especially with younger users. Nearly everyone uses YouTube, and they spend significantly more time on it than on Google.
Also, specialized search engines like Autotrader for used cars and Amazon for ecommerce have captured significant market share in their respective categories.
This fragmentation means that conscious decisions about platform optimization become increasingly important. Different platforms serve different demographics and purposes, requiring strategic choices about where to invest optimization efforts.
I asked Stephen if he thought Google’s dominance was under threat, or if it would remain part of a fractured search journey. But, he thought Google would be relevant for at least half a decade to come.
“I don’t see Google going anywhere. And I also don’t see the massive difference in LLM optimization. So most of the things that you would be doing for Google now … are broadly marketing things anyway and broadly impact LLM optimization.”
LLM Optimization Could Be A Return To Traditional Marketing
Looking toward AI-driven search platforms, Stephen believes the same brand-building tactics that work for Google will prove effective across LLM platforms. These new platforms don’t necessarily demand new rules; they reinforce old ones.
“What works in Google now, broadly speaking, is good marketing. That also applies to LLMs,” he said.
While we’re still learning how LLMs surface content and determine authority, early indicators suggest trust signals, brand presence, and real-world engagement all play pivotal roles.
The key insight is that LLM optimization doesn’t require entirely new approaches but rather a return to fundamental marketing principles focused on audience needs and brand trust.
Television Advertising Creates Significant Impact
I asked Stephen what he would do if he were to launch a new brand and how he would quickly gain traction.
In an interesting twist for someone who has worked in the SEO industry for so long, he cited TV as his primary focus.
“I’d build a transactional website and spend millions on TV [advertising]. If I did more [marketing], I’d add PR.” Stephen told me.
This recommendation reflects his belief that traditional marketing channels create a significant impact.
He believes, the combination of a functional ecommerce website with substantial television advertising investment, supplemented by PR activities, provides the foundation for rapid brand recognition and search visibility.
Before We Ruined The Internet
To me, it feels like we are going full circle and back to the days prior to the introduction of “new media” in the early 90s, when TV advertising was dominant and offline advertising was heavily influential.
“It’s like we’re going back to before we ruined the internet,” Stephen joked.
In reality, we’re circling back to what always worked: building real brands that people trust, remember, and seek out. The future requires classical marketing principles that prioritize audience understanding and brand building over technical optimization tactics.
This shift benefits the entire marketing industry by encouraging more integrated approaches that consider the complete customer journey rather than isolated technical optimizations.
Success in both search and LLM platforms increasingly depends on building genuine brand recognition and trust through consistent, audience-focused marketing activities across multiple channels.
Whether it’s Google, Bing, an LLM, or something we haven’t seen yet, brand is the one constant that wins.
Thank you to Stephen Kenwright for offering his insights and being my guest on IMHO.
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Featured Image: Shelley Walsh/Search Engine Journal
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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.
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Featured Image: Paulo Bobita/Search Engine Journal
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