Google’s new OKF is hot off the press. There’s a lot of hype around it, so let me explain what it is and why it may matter to you.
An OKF “bundle” is a directory of Markdown files. Each file explains one concept, such as a product, service, policy, or process, and includes a small block of structured information.
The files can link to one another, creating a connected map of what a business consists of.
That map, at least in theory, could make information about a business easier for AI systems to retrieve, connect, and understand—provided the bundle is accessible to those systems.
Why does that matter?
Before the search and retrieval systems behind Google, ChatGPT, Claude, and other AI platforms can explain your business or recommend it to a potential customer, they must first find, read, interpret, and connect information about it.
Making your business easier for these systems to understand is an important part of relevance optimization for the modern search environment.
Some AI systems use retrieval-augmented generation, or RAG, to locate relevant information and incorporate it into a response.
Others use AI agents—software assistants that can decide what to investigate next, compare multiple sources, and complete a sequence of tasks on a user’s behalf.
OKF is designed to help systems like these consume structured knowledge. Because it uses clearly labeled, linked, plain-text files, it can make relationships between products, services, policies, processes, and other concepts easier to interpret.
That could become useful as more prospective customers turn to Google, ChatGPT, Claude, and similar tools to research products, compare services, and identify businesses.
If these systems can access and correctly understand what your company offers, whom it serves, how its services connect, and why it is credible, your business may be better positioned to appear in relevant research and recommendation workflows.
But OKF Is Not a New SEO Requirement
This is where I’d slow down a bit and make sure we’re making a sober, realistic assessment.
OKF came from Google Cloud’s data and analytics organization, not the Google Search team.
Google has not announced OKF as:
A ranking factor
An AI Overview requirement
An AI Mode optimization feature
A crawler directive
A replacement for schema markup, XML sitemaps, or normal web pages
Does that mean OKF is irrelevant? Absolutely not.
In fact, one could argue that one should not expect Google to tell the whole truth about how to manipulate its systems to rank and recommend you more.
But the fact remains that you should treat any claim that publishing an OKF folder will improve rankings or earn more ChatGPT and Google AI citations as speculation.
This may become a confirmed future use case, but it has not been proven.
Does Your Business Need OKF?
For most small and midsize businesses, my answer today is:
Probably not yet.
A local contractor with weak service pages, inconsistent business information, poor reviews, and indexing problems will not fix those issues by creating an OKF bundle.
The same applies to a professional-services company whose website does not clearly explain who it serves, what it does, where it operates, or why a buyer should trust it.
OKF becomes more relevant when a company:
Has large amounts of valuable knowledge spread across several systems
Is actively developing internal or customer-facing AI agents
Maintains extensive technical documentation, datasets, APIs, or product information
The Bigger SEO and AEO Lesson
Although most businesses probably don’t need to implement OKF today, they should pay attention to what it represents.
My larger takeaway, which hopefully you can also recognize, is that search has moved beyond finding pages that mention the correct words.
AI systems increasingly need to retrieve specific facts, understand how those facts relate, determine which version is current and reliable, and assemble the information into an answer or action on behalf of users.
Your competitive advantage is therefore becoming less about publishing the highest number of pages and more about maintaining the clearest, most reputable, best-connected source of truth.
If you want the short version, here’s what I’m seeing right now. Local SEO is still very much alive, but the way people discover and choose local businesses is changing. Google is moving toward a more conversational, AI-engine experience, so it’s not enough to just rank anymore. Your business also needs to be easy for Google to understand, easy for AI systems to summarize, and easy for real people to trust. I recently sat down with Darren Shaw from Whitespark, and the conversation reminded me why local SEO is still one of the most valuable parts of search.
Darren has been in this space long enough to see local search evolve from simple map pack tactics into a much more sophisticated system of proximity, relevance, reviews, business data, and now AI recommendations. That kind of perspective matters to me. A lot of people in SEO get distracted by the latest acronym or trend, but what I appreciate about Darren is that he has seen enough cycles to know what actually holds up over time.
The main takeaway of the conversation was pretty simple. AI is changing the way people experience search, but it is not replacing strong local SEO fundamentals. If anything, it is making them even more important.
The local search interface is changing
The local search interface is changing because people are no longer limited to short keyword searches like “plumber near me” or “dentist Dallas.” They are asking longer, more specific questions. They want recommendations based on urgency, preference, trust, location, availability, and context.
That changes the job of local SEO. For a long time, local SEO was mostly about ranking in the local pack for short keywords. I still think that matters. I just don’t think it tells the whole story anymore. In an AI search environment, the bigger question is whether the system understands your business well enough to recommend it in the right situation. That’s why I think Google’s Ask Maps feature matters. Google is turning Maps into a Gemini-powered conversational experience where people can ask real-world questions about places and get personalized recommendations based on Maps data. To me, that’s a pretty clear signal. Maps is becoming more than a directory. It’s becoming an AI search layer that helps people make real-world decisions.
When I look at a search like finding a nearby dentist who is good with anxious patients and offers evening appointments, I see a very different kind of intent than a simple “dentist near me” search. The practice that wins that query is usually not just the one closest to the person searching. It is the one with the clearest service information, the strongest reviews, useful supporting content, and enough trust signals that Google feels confident recommending it. That’s where local SEO is headed.
Local SEO was never just about ranking
I never viewed local SEO as just a rankings play. A local business does not win because it shows up. It wins when someone chooses it. Rankings give you visibility. Selection is what turns that visibility into revenue.
That’s where I see a lot of businesses get stuck. They obsess over where they appear and ignore how they look when a real customer starts comparing options. You can rank well and still lose the lead if your Google Business Profile feels thin, your reviews do not build trust, your photos look outdated, or your service details do not answer the question the buyer actually has. That matters even more now because AI-driven local search is not just about retrieving businesses. It is comparing them. It is summarizing them. It is trying to decide which option looks most useful for the person searching. So when I look at local visibility, I want a business to be built for both retrieval and preference. Retrieval means Google can find it and understand it. Preference means the system has enough confidence to show it as the better fit. That’s the standard I care about.
Reviews are one of the strongest trust layers in local SEO
I think reviews are one of the strongest trust layers in local SEO because they influence both rankings and conversions. Darren made that point clearly in our conversation, and I agree with him completely. A lot of business owners still think about reviews as reputation management. That is part of it, but it’s not the whole story. Reviews are also content. They capture the real customer experience in natural language. People talk about services, staff, neighborhoods, problems, outcomes, wait times, pricing concerns, and the reasons they chose that business in the first place. That kind of language helps customers decide, but it also helps search systems understand the business at a deeper level. If patients keep saying a dental office is great with nervous patients, that is a meaningful signal. If homeowners keep mentioning emergency roof repair after storms, that matters too. If restaurant customers keep bringing up gluten-free options, fast service, parking, or atmosphere, that gives useful context. I think this matters even more in AI local search because the query is getting more conversational. People are not just searching for a category anymore. They’re looking for the right fit.
Review recency matters more than most businesses realize
Review recency matters more than most businesses realize because customers and search systems both care about what’s happening now. A business with a large review count but no recent activity can look stale. A business with fewer total reviews but consistent new reviews can look active, trusted, and relevant.
That does not mean businesses should chase reviews in a sloppy or aggressive way. It means review generation should become part of the operating process. Ask at the right time. Make it easy. Train the team. Use a simple review link or QR code when appropriate. Follow up naturally. Keep the process tied to real customer experience. The mistake is treating reviews like a one-time campaign. Reviews should be a steady signal that the business is active, trusted, and still delivering. That is especially important in competitive local markets where every business claims to be the best. Reviews give buyers and AI systems a stronger reason to believe one business over another.
Your Google Business Profile has to be built like a conversion asset
I look at a Google Business Profile as a conversion asset, not a box to check. A lot of local buyers decide who to call before they ever spend much time on a website, so the profile itself has to help you win the click, the call, or the visit.
That is one reason local SEO has been more protected from AI disruption than pure informational SEO. If someone wants a definition or a basic how-to answer, AI may handle that without sending the user anywhere. But if someone needs a dentist, lawyer, plumber, med spa, restaurant, HVAC company, or roofer, they still have to choose a real business. And a lot of that choice happens inside Google. Your categories, services, products, photos, reviews, posts, hours, attributes, and business description all shape that decision. Some of those elements can affect rankings. Others do more of the conversion work. I care about both. I see too many businesses treat their Google Business Profile like a one-time setup task. They choose a category once, add a few photos, write a generic description, and move on. Then they wonder why competitors with stronger profiles keep getting the calls. That’s not how I approach it. If your profile is one of the main places customers compare you, it needs to be built intentionally and managed like a living visibility asset.
Categories can quietly make or break local visibility
Categories are one of those local SEO details that seem small until they start costing a business real visibility. I check them early because they tell Google what kind of business it is. If the primary category is too broad or just not aligned with the core offer, you can create a relevance problem before anything else even gets a chance to help.
I see this a lot. A law firm selects “law firm” when the better fit might be personal injury attorney, criminal justice attorney, or bankruptcy attorney. A dental practice might not reflect the services it actually wants to be found for, which means it can miss visibility for higher-intent searches tied to emergency dentistry, cosmetic dentistry, implants, or orthodontics. This is one of the first things I look at in a local SEO audit because it’s simple, but the impact can be significant. The primary category needs to match the main thing the business wants to be found for. Then the supporting categories, services, website content, reviews, and citations all need to reinforce that same relevance. That’s how I help close the gap between what a business offers and what Google understands.
Citations are still useful, but they are not a magic shortcut
Citations still matter, sure, but I don’t look at them as the shortcut they used to be in local SEO.
I think of them as trust and legitimacy signals. If a business only shows up on its website and Google Business Profile, that’s a pretty thin footprint. If the same business information shows up consistently across major directories, industry platforms, local sources, review sites, and other trusted third-party profiles, the business looks more established and easier to verify. I think that matters for Google. I also think it matters even more as AI systems take a bigger role in local discovery. What I would not do is push a business into hundreds of weak directories just to inflate the count. I would focus on building a clean, consistent presence in the places that actually matter. That usually means major business directories, relevant local sites, industry-specific platforms, review sources, and professional associations. The right mix depends on the business. If I am working with a lawyer, I am looking at legal directories. If it is a dentist, I want healthcare-related profiles. If it is a home services company, I am thinking about home services platforms, local associations, and trade directories. I am not after volume here. I am after confidence.
AI local search rewards complete information
AI local search rewards complete information because conversational searches need more context.
A short keyword search might only need a service and a location. But if someone is looking for the best emergency plumber nearby who can come out tonight and has strong reviews, the system has a lot more to evaluate. It has to understand the service, the urgency, the area, the availability, the review quality, and whether the business looks trustworthy. If your business does not communicate those details clearly, you are asking Google and AI tools to fill in the blanks. I do not like building marketing strategies around guesswork. I would rather feed the system better information. That starts with the basics. I want the website to answer real buyer questions. I want the Google Business Profile to list clear services. I want reviews that are recent and specific. I want citations to stay consistent. I want photos that build trust. And I want the content to explain who the business helps, what it does, where it works, and why someone should choose it. This is not about stuffing keywords into every sentence. It is about making the business easier to retrieve, understand, compare, and recommend. That is the difference I see between old local SEO and local SEO built for AI search.
Old SEO tactics are not enough by themselves
Old SEO tactics are not enough on their own anymore, especially in local search. Google is doing more than matching words. It’s getting more interpretive. It’s trying to understand the business itself, the context around the search, the evidence behind the claims, the sentiment around the brand, and whether the fit is actually right for that customer’s need.
That does not make traditional SEO useless. I still care about the fundamentals. Technical health matters. Crawlable pages matter. Strong content matters. Internal linking, backlinks, local relevance, and clean business data all still do real work. But now I see those pieces as support for something bigger. I am not just asking if a business can rank for a keyword. I am asking if Google would feel confident recommending that business for a specific situation. That shift changes how I approach local strategy. A generic service page is not enough. A thin Google Business Profile is not enough. A few old reviews are not enough. A list of locations without real local proof is not enough. If a business wants to win, it has to become the clearest and most credible answer for the situations it wants to own. That’s the work.
The biggest opportunity is fixing selection, not just visibility
The biggest opportunity is fixing selection, not just visibility. Most businesses want more rankings, but many of them are already leaking leads from the visibility they have.
If your profile gets impressions but few calls, that is a selection problem. If people click your profile but choose a competitor, that is a selection problem. If you rank locally but your reviews, photos, services, and website do not build confidence, that is a selection problem. This is why I don’t separate SEO from conversion. A stronger review profile can improve trust. Better photos can reduce hesitation. Clearer services can increase relevance. Better website content can support both users and AI systems. Stronger citations can reinforce legitimacy. A better Google Business Profile can turn more visibility into actual leads. That is how local SEO should be judged. Not just “Did rankings move?” The better question is, “Did the business become easier to find, trust, and choose?
Local SEO is getting more conversational, more personalized, and more influenced by AI, but the goal is still the same. I want the right customers to find your business, trust what they see, and feel confident choosing you.
What has changed is the standard. If you want to show up well in AI local search, your business needs complete information, recent reviews, accurate categories, clear service details, consistent listings, and content that answers the real questions people ask before they ever contact you. If you want a practical game plan, schedule a call with me. I’ll show you where your local visibility is leaking, what is keeping your business from being preferred, and which fixes I would prioritize first.
In a recent video interview, which you can find on my YouTube channel, Mitko asked me why it is that so many people say that “SEO didn’t work” for them.
A lot of businesses think search is supposed to reward them quickly just because they made changes, published content, or hired somebody to “do SEO.” That is not really how Google operates.
In fact, one of the biggest mistakes I see is people expecting fast, clean, obvious feedback from a system that is built to be cautious, suspicious of manipulation, and slow to hand out trust.
That is the frame I want people to understand.
I talk about this in the above recent YouTube video.
In the video, I talked about a Google patent that gets at this idea directly. The core point is that when changes are made to a document or a site, Google may not just cleanly move that page from old rank to new rank in a straight line. There can be a transition period. And during that transition period, the response can look delayed, negative, random, or just unexpected.
That part matters a lot.
Because what most businesses want is this: “I made the optimization, so now show me the reward.”
But what Google seems to be saying is closer to this: “You made a change. Fine. I am still going to watch it. I am still going to test it. I am still going to make sure I am not being manipulated.”
That is a completely different mindset.
And once you understand that, a lot of what confuses people starts to make more sense.
So when I look at Google, I do not look at it like some simple machine where you press a button and get a ranking. I look at it more like a system that is trying to protect itself. It wants to separate genuine value from manipulation. It wants to avoid being gamed. It wants to see what holds up.
And if that is how the system operates, then the businesses that win are usually not the ones chasing instant movement. They are the ones doing steady, credible, useful work long enough for trust to build.
That is the foundation.
And once you understand that foundation, thenext two shifts matter even more.
Why TurboQuant Matters More Than It Sounds
Now let’s build on that.
If Google is already operating from a place of caution and trust, then the next big question is how it gets better at understanding meaning, intent, and usefulness at scale. That is where TurboQuant gets interesting.
The simple version is that TurboQuant points to AI search getting much faster and more efficient at handling vector search. In plain English, that means better semantic understanding across huge amounts of information. It means systems can process meaning more efficiently instead of relying so heavily on simple term matching and slower methods.
What gets my attention here is not just the technical side of it. It is what it suggests about where search is going.
If Google gets faster at building and using these semantic representations, then it gets better at understanding what a person is actually looking for, not just what exact words they typed. It also gets better at pulling from a much larger pool of relevant information when deciding what to surface.
That raises the standard.
Because now it is not enough to just have a page that mentions the right terms. It is not enough to sound vaguely relevant. The system is moving more toward understanding whether your page actually helps with the need behind the query.
That is a big difference.
So when I look at something like TurboQuant, I do not see it as some separate “AI thing” over here and SEO over there. I see it as part of the same direction Google has been moving in for years. Better understanding. Better retrieval. Better intent matching. Better filtering of weak, generic, copycat content.
And that brings more pressure, not less.
You do not respond to this by pumping out more empty pages. You respond by making your content more answer-ready, more credible, and more tightly aligned with what real people and AI engines are looking for. You reduce fluff. You improve structure. You make your pages easier to understand. You make the value obvious.
That is what I think a lot of people miss when they hear about new search technology. They want a trick. They want a shortcut. But most of the time, what these changes really do is increase the reward for clarity and increase the penalty for weak thinking.
Why ChatGPT Just Became a Bigger Product-Discovery Surface
Now, here is the other shift brands need to pay attention to.
ChatGPT just became a more serious place for product discovery.
With the richer shopping experience that rolled out in late March, users can now begin to browse more visually, compare products side by side, and move through product consideration in a much more direct way inside ChatGPT itself. To me, that matters because AI visibility is not just about being cited anymore. It is increasingly about being considered.
That is a different stage of the journey.
A lot of brands are still thinking, “Do I show up?” But that is too basic now. The better question is, “When I do show up, can I be understood, compared, and chosen?”
Because that is where this is going.
If a person is using ChatGPT to explore products, compare options, and narrow decisions, then your visibility problem is no longer just a traffic problem. It is a retrieval and consideration problem.
Can the system pull in the right information about what you sell? Can it understand what makes your product different? Can it present your offer in a way that makes sense next to alternatives?
If not, you are leaking visibility at the exact moment somebody is trying to make a decision.
And this is where I think the connection becomes really clear.
Google’s operating logic has long been about resisting manipulation and trying to reward actual value over time.
New developments like TurboQuant suggest search systems are getting faster and better at understanding meaning and intent.
And now ChatGPT is becoming a stronger environment for product comparison and discovery.
Put all of that together, and the pattern is obvious.
The brands that win are not going to be the ones relying on shallow tactics, inflated claims, or messy pages that make people work to understand them. The brands that win are going to be easier to retrieve, easier to understand, easier to compare, and easier to trust.
That is the real shift.
So if I am looking at a brand right now, I am asking a few simple questions:
Is the message clear?
Is the offer easy to understand?
Is the content genuinely useful?
Are the pages structured in a way that helps both humans and machines?
When somebody compares this brand to alternatives, is there a strong reason to choose it?
Because search is not just a ranking environment anymore. It is becoming more of a retrieval, evaluation, and selection environment. And honestly, that has been building for a while. It is just getting harder to ignore now.
Be clearer. Be more useful. Be more credible. Be easier to understand. And stop expecting a trust-based system to behave like a vending machine.
That is the mindset shift.
And the businesses that make that shift early are going to be in a much better position than the ones still waiting for instant feedback from systems that aren’t designed to work that way.
If you want to win in AI search, you have to win two distinct, but related arenas. Getting retrieved and getting preferred.
I don’t treat AI visibility like a vanity ranking game. I care more about whether a brand is consistently pulled into the right conversations and preferred for high intent prompts.
The research supports that approach. The 2023 GEO study introduced Generative Engine Optimization and reported visibility gains of up to 40% from the right optimization methods.
First, your brand has to get retrieved. That means your site, brand, or page has to make it into the possible answer set. Then, once you are in the set, you have to get preferred. That second step is the re-ranking layer, where the model decides which option is the clearest fit for the user’s prompt. The 2025 E-GEO paper formalizes that same retrieval-plus-ranking framework.
That is why I don’t separate off-page SEO from on-page AI optimization. Off-page authority, mentions, citations, links, and digital PR help you get pulled in. Clear, well-structured, evidence backed content helps you get chosen once you are there.
I do not chase vanity rankings. Ranking for a head term like IT managed services might look good in a dashboard, but it tells me almost nothing about whether I am visible when a real buyer is actually close to choosing a provider.
People looking to purchase are not stopping at short category phrases anymore. They are asking long, detailed, constraint-heavy buying questions like:
“We run a 12-location healthcare group in Dallas and need a HIPAA-compliant IT provider that can manage endpoints, harden Microsoft 365, support audits, and help with compliance documentation. Who should we talk to?”
“Which Dallas managed IT companies can provide backup and disaster recovery with a one-hour recovery time objective, a 15-minute recovery point objective, and 24/7 incident response?”
“We need a managed cybersecurity partner for a multi-site medical practice that can handle SIEM, endpoint detection, phishing training, and policy documentation. Who actually does all of that well?”
This shift is not a theory anymore. Amazon says shoppers are already using Rufus to type natural-language questions, compare options, and ask granular product questions, while Bain found that 42% of large language model users already use these platforms for shopping recommendations.
In other words, I care less about whether I “rank #1” for a trophy keyword and more about whether search engines and large language models consistently understand that my brand is a strong answer for the high-intent situations my market actually cares about. That is what matters.
The process I use to increase AI visibility
My process starts with query selection, not page editing.
First, I identify the money prompts. These are the commercial, comparison-driven, bottom-of-funnel queries that reflect how people actually ask for help today. Then I expand those into related prompt variations so I can see the full intent map around the topic.
After that, I compare my page against competing pages and measure which page is most semantically aligned to the query. If my page is weak, I do not guess why. I fix the relevance gap.
Then I optimize at the chunk level.
Modern AI systems often retrieve and reuse sections, not entire pages. That is why I built an internal workflow that pulls strong content chunks, scores them against the target query, rewrites the best chunk into cleaner formats, and then re-ranks the outputs to identify the version most likely to be extracted and preferred.
In practice, the best version is usually the one that is easiest to scan, easiest to trust, and easiest to quote.
What I like about the 2025 E-GEO study is that it pushes the conversation beyond hype.
The researchers tested more than 7,000 realistic product queries, evaluated 15 common rewriting heuristics, and found that the best results came from a stable pattern rather than a gimmick. The content that rose tended to align closely with user intent, preserve factual accuracy, clearly differentiate itself, and present information in a format that is easy for the model to process.
I have had conversations in person and even on my YouTube channel with industry-leading colleagues like Nick Eubanks, Ross Simmonds, and Charles Floate, and even when the tactics vary, the same fundamentals keep coming up: build authority beyond your site, understand how people really search, and publish content that is clear enough to be reused in answers.
That is a big reason I believe AI visibility is not a trick. It is a discipline.
You need distribution. You need credibility. You need answer-ready content. And you need to stop measuring success with outdated vanity metrics that were built for a different search era.
AI visibility is not about gaming one prompt or chasing one keyword. It is about increasing the probability that your brand gets retrieved for the right conversations and is preferred when the model compares options.
Parent/head terms still matter as category and entity anchors for retrieval, internal linking, and query reformulation, but they do not deserve to be your primary measurement system for AI-era revenue visibility.
The KPI should be whether your brand is retrieved and preferred across the high-intent prompt set that real buyers actually use.
That means winning both arenas: off-page presence strong enough to get you into the set, and on-page structure strong enough to move you to the top.
That’s the process I use, and it’s the process I keep seeing validated by research, by testing, and by conversations with other people deep in this space. If you focus on those fundamentals, you stop chasing vanity and start building visibility that actually compounds. Schedule an introductory call with me today to discuss how we can do this for your brand.
A 2025 research study from researchers at MIT and Columbia University tested what actually moves content up in AI-generated rankings. Their big finding wasn’t “use this one weird prompt.” It was that repeatable, reliable gains come from a consistent structure: match user intent, stay factual, show clear differentiation, use evidence, and format content so it’s easy to extract.
I built a custom internal tool inspired by that study to help me (and my clients) turn messy, long-form information into “AI-ready” answer blocks that are more likely to be pulled and preferred in AI results. We’re actively expanding that tool to make it more comprehensive, and it’s already being used to guide client content.
I’ve spent the last couple of years watching the same pattern play out across industries:
Some brands get mentioned in AI answers… but show up as the third or fourth recommendation.
Others get pulled sometimes… but inconsistently.
And a few dominate because their content is the easiest to trust, quote, and rank.
That’s why I pay attention when researchers publish something that goes beyond opinions and actually tests what works.
The research team from MIT and Columbia University ran the study (E-GEO: A Testbed for Generative Engine Optimization in E-Commerce) to measure how answer engine rankings change based on how content is written. They used thousands of real-world shopping-style queries, rewrote product descriptions using different approaches, and tracked whether the rewritten versions moved up or down in AI rankings.
What I’m sharing below is the practical version of what matters, and how you can apply it whether you sell products or services.
The two-step reality: getting pulled vs getting preferred
Most brands only think about one part of the problem.
Step 1: Retrieval (getting pulled in)
This is whether your page, brand, or product even gets included as a possible answer.
Step 2: Re-ranking (getting preferred)
This is where the AI decides what’s “best,” “second best,” and so on.
The 2025 study focused heavily on that second step: once options are in the set, what makes one rise to the top?
If you’re investing in content for AI visibility, you want both:
● content that reliably gets pulled ● content that reliably gets ranked as the preferred option
What the researchers actually did (in plain English)
Here’s the simple version of the test:
They took 7,000+ real “what should I buy?” style posts from Reddit.
They matched each query to the 10 most relevant Amazon product listings using a semantic similarity method (basically, “meaning match,” not just keyword match).
They rewrote product descriptions using different prompt styles.
They measured whether the rewritten descriptions moved up in the AI’s ranking.
They then used a second model to iteratively improve the rewrite prompts until the rewrites performed better.
The purpose wasn’t to find a trick. It was to find patterns that hold up repeatedly across many queries and products.
That’s exactly what brands need right now, repeatable rules, not hype.
The most important practical takeaway
AI rankings reward content that makes it easy to confidently choose and easy to quote.
That’s why the winning patterns consistently included:
1) Clear intent match
The best-performing rewrites aligned tightly with what the user actually asked for, especially long, conversational queries with constraints.
Not “Knife set for kitchen.”
More like: “Premium durable knife set with minimal upkeep needed.”
That shift matters because it directly mirrors the user’s real goal.
2) Factual grounding
One of the most consistent themes was factuality. Keep claims accurate, avoid embellishment, and preserve what can be supported.
In real life, that means:
● don’t guess ● don’t inflate benefits ● don’t claim “best” without support
3) Clear differentiation (your “why us” without fluff)
Competitive positioning mattered, especially when it was expressed as concrete differences, not generic marketing language.
Examples:
● materials, specs, certifications ● what’s included vs not included ● warranty terms ● durability, maintenance requirements ● constraints the product/service is best for (and not best for)
4) Evidence signals
When you can back something up with data or reputable references, do it. Evidence helps the AI system “trust” the content and reuse it.
For service businesses, evidence can be:
● licensing and certifications ● documented process steps ● before/after metrics ● review volume and rating ● pricing ranges and what drives them
5) Scannable formatting
This one is huge, and it matches what I’ve seen in the wild. Content that’s easy to scan is easier for AI systems to lift into answers.
Headings, bullets, short blocks, ranges, and direct definitions beat long paragraphs every time.
What didn’t work as well
A lot of “internet advice” about AI visibility leans into tone or style:
● “Write like an ad” ● “Be super persuasive” ● “Tell a story” ● “Sound authoritative”
The study showed that these approaches can be inconsistent and, in some cases, can even hurt performance if they reduce factual clarity or drift away from the user’s intent.
The takeaway: style is secondary; structure and usefulness come first.
The custom tool I built (inspired by the study)
This study didn’t just confirm what I suspected; it gave me a structure I could build around.
So I built an internal GPT-powered re-ranking workflow inspired by the study’s re-ranking logic.
Here’s what it does in practical terms:
What my tool does today
I feed it a target query (example: “How much does carpet cleaning cost in Northern Virginia?”).
It ingests multiple content “chunks” pulled from top-performing pages on Google.
It ranks those chunks based on which one most directly and completely answers the query.
It rewrites the best chunk into multiple output formats, especially.
It re-ranks the outputs and recommends the version most likely to be extractable and preferred in AI answers.
In short, it helps us consistently produce content that is accurate, aligned with intent, and formatted for extraction, which is exactly what the study suggests is repeatably effective.
How we’re expanding it
Right now we’re expanding the workflow to be more iterative and mathematical about which content is most optimized. This will result in:
● content that more accurately reflects what AI engines reward ● stronger evidence handling ● consistency checks ● broader content formats
How we’re using it for clients
We’re already using this tool in our client work to:
● upgrade existing pages into AI-ready “answer-first” structures ● produce scannable sections that AI engines can quote cleanly ● reduce fluff while increasing proof and clarity ● align content with how people actually ask questions in AI tools
This is one of the ways we’ve been able to move faster while staying grounded and factual, because the tool forces discipline around intent, structure, and evidence.
Final thoughts
The 2025 MIT + Columbia E-GEO study supports something I’ve been emphasizing for a while:
If you want to rank well in AI answers, your content has to do more than “sound good.” It has to be the clearest match to the user’s intent, backed by facts, and formatted in a way that’s easy to extract and trust.
That’s why I built a tool around this and why we’re expanding it and using it actively in client content.
If you want your site to show up more often and be preferred in AI answers, request my free AI visibility checklist. I’ll review your site and tell you:
● what’s preventing AI engines from pulling your pages ● what’s keeping you from being ranked as the “top” recommendation ● which pages to fix first for the fastest impact
You can implement the changes yourself, or my team at SEO Rank Media can handle it for you.
Remember the good days of SEO? Where you could cram in a few related keywords into your website content, and Google would (maybe) reward you with top-ranking glory?
These were simpler times, and now we unfortunately find ourselves waving goodbye to the simplicity of it all. These days, AI-driven search tools like those found in ChatGPT, Claude, and Perplexity are rewriting the playbook (or just setting it on fire).
For businesses, the SEO game has changed.
It’s not just businesses pulling their collective hair out over this. Searching online as a regular human being has turned into an Olympic-level patience test. You type a question into Google, and rather than getting a helpful answer, you’re bombarded with ads masquerading as advice. Those of us who have recently made use of AI-driven search have discovered a little secret: AI can sometimes answer our questions better than Google ever could.
Welcome to the Future of Search (or How We All Lost Our Minds)
So, how do we fix this? Well, we don’t. Instead, we adapt to this new wave of search technology that’s fast becoming a survival strategy for brands that need to stay relevant.
Say hello to Generative Engine Optimization (GEO) — a new lifeline for traditional SEO experts feeling the sting of AI-driven search. GEO offers more than merely surviving the noise; it allows your brand to stand out where it matters the most, with visibility that actually counts.
The G.E.O.D.A.T.A Framework from SEO Rank Media is a seven-step strategy that covers everything from ensuring bots can crawl your content to dealing with those AI “hallucinations” where facts go to die.
Instead of fighting the system, make it work for you. If you’re ready to drop the SEO tricks of yesterday and learn more about GEO, let’s get started.
The G.E.O.D.A.T.A. Framework
AI search platforms like ChatGPT, Claude, and Perplexity have opened up a whole new world for businesses to connect with audiences. Sounds great, right? But here’s the twist—this isn’t “business as usual” SEO anymore.
If your strategy is still clinging to Google SERPs like a security blanket, you’re already behind the curve.
That’s where the G.E.O.D.A.T.A. Framework comes in. Developed by SEO Rank Media, the framework gives your business a head start in the AI-driven search arena.
What makes the G.E.O.D.A.T.A. Framework different?
Practical from Day One: Each step is clear and actionable—you can actually do something with it.
Bigger Than AI Rankings: Sharpen your overall marketing game.
Team-Friendly: Easy enough to explain to your boss, clients, or that one coworker who still doesn’t “get” AI.
Why Bother with a Framework?
The field is no longer about simply “ranking in Google.” Today’s search environment demands leadership and strategy. Brands need guidance to navigate the following:
How to perform across multiple AI search platforms.
What kind of content to produce to engage these platforms.
Where and how to distribute content to maximize visibility.
The Steps of G.E.O.D.A.T.A.
The framework outlines a step-by-step process to align your content and search strategies with the AI-dominated world. Each step builds on the last to ensure your brand is positioned for success:
Gather Intelligence – Know what’s happening in the AI search world.
Evaluate Accessibility – Make sure bots can actually find your stuff (duh).
Optimize Brand Presence – Be unforgettable, or at least noticeable.
Develop Sentiment – Build a brand people (and AI) actually like.
Analyze Competitors – See what’s working for them and learn.
Target Data Sources – Be where the algorithms are pulling from.
Answer Accurately—Deliver real answers, not fluff.
1. Gather Intelligence
Tools like ChatGPT and Claude are shaping the way people perceive your business, whether you’re aware of it or not. So, understanding how these AI platforms view your brand is a big deal. If AI gets it wrong, like misrepresenting your brand or offering answers that aren’t very accurate, you’re left with customers who are judging your offerings based on bad info.
So, how do these AI platforms know what to say about you? It all comes down to the data they have been trained on. AI pulls from all sorts of sources, including:
Websites, blogs, and forums (including user-generated forums).
AI synthesizes all this information and uses it to generate answers. The quality of those answers depends heavily on the data available. If your brand isn’t well-represented, or worse, represented inaccurately, the AI delivers those misleading results—with confidence.
So the first step is simple: start asking questions. Fire up an AI tool like ChatGPT and test the waters with queries like:
“What is [Your Brand]?
“What does [Your Brand] offer?
Is [Your Brand] trustworthy?”
Pay close attention. Does the AI accurately summarize your business? Are there outright inaccuracies?
Armed with these insights, you can identify where your messaging needs to improve and take steps to fix it. This isn’t guesswork; it’s actionable intelligence and the very foundation of effective GEO.
2. Evaluate Accessibility
There’s been a lot of chatter lately about blocking AI from crawling websites—like letting bots read public information somehow equals grand theft of data. Unless you’re sitting on government secrets (which shouldn’t really be public in the first place), blocking AI does more harm than good.
AI platforms use bots to crawl sites to get data for their models, the same way Google does. The difference is Google relies on structured indexing, and AI pulls data from a wider range of sources.
If you want to show up in AI search results, then you need to give these bots access to your page. It’s as simple as that.
Start by checking your robots.txt, the gatekeeper for bots. This file tells crawlers what they can and can’t access. Yes, it is smart to block some bots to save resources or secure sensitive areas; just make sure you’re not accidentally excluding AI too.
It’s likely you’re no stranger to how important brand presence is when it comes to SEO. AI platforms pull all of the information they find online and use it to understand and then represent your business when a user searches for it.
If your messaging is long-winded, vague, inconsistent, or missing, you’re risking misrepresentation, or worse, being completely ignored.
Your landing pages need a very frank and straightforward brand statement that answers the basics:
Who you are: “[Your brand] leads the way in sustainable home goods.”
What you do: “We create eco-friendly furniture for modern living.”
Why you’re different: “Our designs combine style, sustainability, and affordability.”
Make sure this messaging is everywhere AI platforms might be looking. Put it on your website, LinkedIn, and social media, and review responses, as AI will draw answers from a multitude of sources.
Consistency is what gets your brand represented the way you want, and not as some random mashup of outdated info. Set the record straight before anyone can even get the wrong idea.
4. Develop Sentiment
AI platforms don’t just pull out the facts; they piece together a brand’s overall vibe from an array of sources: forums, reviews, and social media. The catch is that bad press tends to stick around like gum on a shoe.
Take AT&T, for example: ask ChatGPT about their reliability as a service provider, and you’ll likely hear all about their 2024 outage alongside mentions of their reliability. Ouch.
Now, compare that to CrowdStrike. Despite their infamous broken Windows update causing probably the biggest global IT outage in history, you won’t see AI harping on it.
Why? They have absolutely mastered sentiment management, strategically flooding the digital space with positive content and well-managed review responses that overshadow their epic blunder.
If you want AI to focus on your wins, start by testing how platforms portray your brand. Ask questions like “Is [Your Brand] reliable?” Spot the negatives and tackle them head-on with corrective content.
Strong sentiment GEO means that when people search for your brand, they see your strengths and not your stumbles.
5. Analyze Competitors
Keeping tabs on your competitors in the SEO world is a necessary evil, but with AI, it becomes a whole lot easier to see just where your business could sit in rankings.
AI rankings heavily influence user decisions, especially for the juicy middle-of-funnel searches like “Best in [location]” or “Top providers for [service].” Having an understanding of how your business stacks up against the competition reveals where you can step up your game, be more visible, and take your place in the share of the market.
Start by identifying the key competitive queries that are relevant to your industry. AI tools like ChatGPT make this quite easy, but for the best results, use a GEO service like SEO Rank Media to map out how competitors are ranking.
With this intel, it’s time to take action. Create content that answers these questions better than anyone else. Use clear, direct language, highlight your benefits, and make sure your expertise comes through in a specific way AI platforms recognize.
The goal here is to make sure your brand is the obvious choice for these searches.
AI platforms don’t just make things up (well, most of the time), they draw from trusted data sources like LinkedIn, GitHub, and even Reddit to create their responses. If you want your brand to show up in those results, you need to meet AI where it’s looking.
Here are a few ways you can improve your visibility:
Publish technical content on GitHub: This platform is a favorite for technical queries, so it’s perfect for showcasing your expertise in a concrete, credible way.
Share insights on LinkedIn: As a part of Microsoft’s ecosystem, LinkedIn is practically a VIP source for professional and industry-specific content.
Have some fun on Reddit: Claude and ChatGPT crawl Subreddits to gain community-driven perspectives. Join in on relevant discussions in an informational (not sales) way to boost your authenticity.
Get strategic in the way you place content, and you’ll ensure your brand’s voice is part of the AI conversation.
7. Answer Accurately
AI “hallucinations” aren’t as fun as they sound. These occur when AI platforms respond with incorrect or misleading information that is so confident it would give Toastmasters a run for their money. Basically, they’re not something you want to happen when someone uses AI to look up your offerings.
The GEO fix for this issue is to create well-structured and relevant FAQ pages that answer critical questions like the following:
“Does [Brand] ship internationally?”
“How does [Brand] handle refunds?”
“What services does [Brand] provide?”
Here’s some proof in the pudding. Taking a look at Ancestry.com’s FAQ page, you can see they have answered commonly asked questions about their service, with one being what do the results tell me?
Jumping onto ChatGPT and asking the question “What do my Ancestry.com results tell me?” yields a result that was quite clearly taken from this FAQ page.
Understanding your audience helps here. You need to know what kind of questions they’re likely going to be typing into an AI search engine and give straightforward and simple answers to them on your website’s FAQ page.
The payoff will be fewer opportunities for hallucinations and a more accurate representation of your business in AI-generated results.
Why GEO is the Way Forward
Let’s be honest: AI search has turned SEO into a wild roller coaster. One minute, you’re impressed by ChatGPT’s ability to summarize complex topics; the next, it’s confidently claiming your brand sells banana-flavored widgets (which, of course, you don’t).
Staying ahead feels like having to learn SEO all over again, but it doesn’t have to.
With SEO Rank Media and the G.E.O.D.A.T.A. Framework, you’ve got a reliable roadmap to tame the chaos and put your brand back in the spotlight. It’s your chance to future-proof your digital strategy, outsmart AI’s quirks, and thrive in this unpredictable search landscape.
Ready to take charge? Let SEO Rank Media help you GEO your way to success.
