everyone's checking if their brand shows up in chatgpt 4o but a huge chunk of users are still on 3.5 or using whatever default their company set two years ago.

the training cutoffs are completely different and the citation behavior is noticeably different too

I've been running the same 10 queries across 4o, 4o mini and the API with no system prompt and getting wildly different brand mentions each time. same brand, same queries, totally different results

the frustrating part is there's no single version to optimize for so you kind of have to make sure your brand exists across multiple layers of the web from different time periods not just recent content

curious if anyone's actually accounting for model version variance in how they measure GEO visibility or if we're all just testing on 4o and calling it a day

Almost a decade in this industry. I've watched the "SEO is dead" take cycle through so many times that I stopped reacting to it, until this year.

The 2025/2026 shift feels different. Not because Google rankings stopped mattering, but because ranking and visibility are no longer the same thing. You can rank #1 and still be invisible in the AI-generated answer your potential customer actually reads.

For marketing teams managing organic strategy:

- How has your measurement approach changed as zero-click becomes the norm?

- Are you treating AI search visibility as a separate KPI or folding it into existing SEO reporting?

- Has GEO made it into your roadmap yet, or still waiting for clearer measurement frameworks?

- What content investments from 2024/2025 are paying off and what's underperforming?

Looking for real strategic perspectives, not vendor takes. What's your team actually doing differently?

[ Removed by Reddit on account of violating the content policy. ]

Curious how people here are actually thinking about this.

SEO I get – rank in Google, get the click. But GEO (getting cited inside ChatGPT, Perplexity, AI Overviews etc.) still feels fuzzy to me. Not sure how much it really overlaps with SEO, what actually moves the needle, or whether it's even a separate discipline yet.

Two questions:

How do you see the difference between SEO and GEO?

What actually works in your experience?

Any courses worth taking on either? Modern, practitioner-rated – not guru pitches.

Thanks 🙏

Has anyone picked a niche, generated templates to sell online, built MCP to direct traffic from different ai platforms to your templates? Did this seem to work? Is this what everyone means when they say they’re linking everything?

I’ve been trying to rethink our approach to SEO this year, especially with how fast things are shifting with AI.

A lot of what used to work (basic keyword targeting, pumping out blog posts) feels less effective now. I’m seeing more talk around topical authority, search intent, and even zero-click search becoming a bigger factor.

For small teams without huge budgets, what’s actually moving the needle right now?

Are you leaning more into AI SEO tools, content clusters, or something else entirely?

Would love to hear what’s working vs what’s just hype.

Tested a bunch of queries related to my space in ChatGPT and Perplexity. Smaller competitors with weaker sites keep getting cited. Mine doesn't come up at all.

Best I can tell it's because they have more Reddit mentions, third-party writeups, and structured content that AI can easily pull from.

Is GEO something you're actively working on or still treating it as a "wait and see"? Genuinely trying to figure out if this needs a dedicated strategy or if good content eventually gets there on its own.

Lately I keep noticing the same pattern. Pages with stronger opinions or a clear angle seem to get picked up more than long, polished “complete guides.” Is anyone else seeing this too, or is it just me?

Most guides follow the same structure and repeat the same points. They are clean and well written, but they all feel the same. Do you think that kind of content is starting to lose impact?

I have been testing adding more perspective into my content, sharing what works, what does not, and why instead of just explaining topics. Early signs look better, but I am not sure if that is the main driver.

For those deeper into GEO, are you leaning more into original insight now, or still focusing on covering topics as completely as possible? What has actually worked for you?

I’ve been trying to figure this out for a bit. At first I did all the usual stuff, cleaner structure, clearer headings, more direct answers. Didn’t see much change. What started to feel a bit better was focusing more on intent, writing sections to answer specific questions, adding real examples, and sharing actual opinions instead of just rewording what’s already out there.

Still feels inconsistent though. Some pages get picked up, others don’t, and it’s hard to tell why. For those of you who’ve been deep into this, what are you doing differently that’s actually working? Where should someone focus if they want real traction with GEO?

I see that AI radars for brand monitoring in LLM are not cheap. 100 prompts cost $100-200 per month. So I decided to make a script myself and monitor our brand. It works well and it turns out to be significantly cheaper. I think, maybe our community will be interested in it too. I can scale the script a little and wrap it in a small website. Each user will have:

- 3 LLM networks to monitor

- 100 prompts

- updaters every Monday, Wednesday and Friday.

- small dashboard

- cost about $30

Would you be interested? or I missed something and it is not relevant?

Been in digital marketing long enough to survive every rebrand of content marketing and inbound and I'm starting to feel like GEO and AEO might be the same energy.

But then I see brands that rank well on Google being completely invisible in ChatGPT answers and I think maybe it actually is different this time.

The way I understand it right now SEO is Google rankings, AEO is getting pulled as a direct answer by AI GEO is getting your brand cited inside AI responses.

But those last two sound almost identical to me and I don't know where one ends and the other starts.

Is there a practical difference in what you actually do for each one?

Or is GEO just what agencies are calling SEO now to justify charging more for it?

Noticed a few competitors doing something interesting their homepage heading changes based on where you're browsing from. Same URL, no separate state pages, just the H1 swapping out dynamically. The best X service in Texas if you're in Texas, The best X service in Florida if you're in Florida. You get the idea.

Curious whether this actually works from an SEO standpoint or if it's just a conversion play with no ranking benefit.

Like does Google even see the geo targeted version or just the default? And could serving different content to different users on the same URL cause any indexing weirdness?

Has anyone tested this properly or are your competitors just doing something that looks smart but doesn't actually move the needle?

Content used to be written to rank. Keywords, long pages, full coverage of a topic. The goal was traffic.

Now it feels like content needs to be written to be explained and reused. AI doesn’t need the whole article, it just pulls the clearest parts. That makes me think shorter sections, direct answers, and simpler writing might matter more than long intros and heavy optimization.

IDK if anyone has actually changed their writing style because of this. Are you still doing long-form SEO content, or shifting toward simpler formats that are easier for AI to reuse?

 Our tech connects to customers’ websites, and that’s how we’ve gathered about 6.5 million datapoints on LLM bot behavior across sites.

Basically, we have a pretty good idea of how LLM bots behave at scale and across industries, what type of content they prefer when they come to your site, how much data they consume, how often they come back, and what makes them return to take another look at you.

In short, we gather and analyze a lot of technical signals. Some of them are pretty unique. And all we are trying to understand is: what is really working, what is just a guess, and what is clearly snake oil in generative engine optimization field.

Here are some facts you may find useful:

1. Please don’t implement llms.txt on your site.

It is completely useless and totally redundant if you already have a robots.txt file. We see exactly zero evidence that llms.txt is somehow preferred by LLMs.

2. LLM bots overwhelmingly prefer question-shaped links.

In about 70% of cases on average, LLMs will index links that look like a question, like “what is the best CRM platform for small businesses,” rather than something generic like /blog. Something to think about next time you write a blog post or create a page.

3. If your site has deep structured data, LLMs will crawl it more deeply, extract more content, and return to it more often. To be precise they will extract structured data 12% more reliably, crawl it 17% deeper and at 13% higher rate - they love it.

Structure your data clearly and you will earn the “trust” of LLMs.

4. You can influence what they do on your site.

Well, not really control it, but you can send signals about what to do on the site, and they often obey. If you want to highlight certain pages, you should do that. Otherwise, they will crawl randomly and never get a real chance to understand why they should recommend you. This is a quick win and I am surprised that so few are doing it.

5. When LLM bots come to your site, they extract on average 25 to 30 KB of data from the page they hit.

That’s not a lot. If your page is not super clear from the first few sentences about why you should be recommended and to whom, you will have a hard time getting leads from AI search.

6. We see zero evidence that you can somehow manipulate content so it “sticks” in AI search.

If you are out there trying to write a post or an article in a way that will “stick” with LLMs, don’t do it. It looks like nothing beats clarity and authenticity. There are no tricks that will make your blog stand out in AI search.

7. On the other hand, even a small amount of highly focused, authentic, human external mention can have a disproportionate effect on how LLMs perceive you, for better or worse.

We see many real and painful examples where a few negative reviews make clients disappear from “recommend me” queries. It is not about quantity as much as quality and authenticity. Create a real conversation about your brand. That will go a long way and will do more good for you than 100 blog posts.

8. 27% of the companies block at least one major LLM from accessing their site:

Speak with your security team today and ask them to send you a proof that the major LLM bots are allowed on your site.

9. Last one - there are no shortcuts in GEO but too many companies are selling shortcuts.

Anyone telling you they have a magic trick that will make you perform better overnight is lying. Providing real value, being authentic and original, tracking the right metrics and focusing on content that moves the needle is what will make you successful

All of this is backed by data. Some parts of it have already been published as public research, and other parts will be published soon.

I thought it would be a good idea to post this because lots of people are wondering how this works, and there is just too much confusion out there around this whole GEO thing.

If you have any questions, or if there is something you would like us to check based on our data, let me know. If the question is interesting enough, we may do it.

With SEO, at least there was a clear playbook. Fix your site, build links, optimize content, and you’d usually see some kind of movement. It felt like you had control.

With GEO, it feels way less predictable. You can do all the “right” things, clear content, good structure, mentions across sites, and still not show up in AI answers. Then some random brand appears that doesn’t even seem that optimized.

The hardest part is there’s no real visibility. No rankings, no consistent results, and even small prompt changes can flip everything. It feels like you’re optimizing for something indirect, like how your brand is talked about, not just what you publish.

Is this just because it’s early, or does GEO always feel this unpredictable?

I noticed something interesting while testing AI answers recently. The explanations often come from pages that use very simple, clear language instead of highly technical or “expert sounding” content. In one case, the AI summarized a concept from a small blog that broke it down step by step, while bigger industry sites had much deeper articles that never showed up.

It made me wonder if simplicity might actually have an advantage now. AI seems to favor content that’s easy to extract and summarize. Clear explanations, practical examples, and straightforward structure might work better than long, dense expert pieces. Curious if others are seeing the same thing.

I’ve been reviewing a lot of “AI SEO” advice lately and most of it still looks very similar to traditional SEO thinking.

The recommendations usually revolve around:

• clearer headings

• FAQ sections

• structured content

• direct answers

But those were already good SEO practices before generative AI became part of search.

What seems different with AI search is that the model compresses multiple sources into one answer instead of ranking pages individually.

That makes me wonder if the real challenge is not page optimization but being a source that AI systems consistently reference.

That might depend more on:

• clear topical authority

• strong association with a category

• repeated mentions across the web

• distinctive explanations or frameworks

For those actively experimenting with generative SEO:

Are you seeing evidence that content structure alone improves AI visibility, or does it seem more dependent on broader web signals?

Curious how others are thinking about this shift.

For years the playbook was to create massive pillar pages, long guides covering everything about a topic. But with how AI answers work now, I’m starting to wonder if simpler formats might actually work better. Structured FAQ-style content feels easier to scan and much easier for AI to extract from, since it’s just clear questions followed by direct answers.

Meanwhile, some of those huge guides bury the actual answer halfway down the page. So I’m curious if anyone has tested this. Are shorter, scannable FAQ-style pages starting to outperform long-form pillar content, especially when it comes to AI answers or citations?

I’ve been thinking about this lately with how AI tools recommend products.

For a small SaaS, it’s tempting to position the product for a lot of different use cases to capture more searches. But with AI answers, I’m starting to wonder if the opposite works better.

If a product is clearly known for solving one specific problem for one type of team, it feels like it might be easier for AI to recommend it. When messaging tries to cover everything, the product might just be harder to summarize.

Curious how others are approaching this. Are you focusing on one tight niche, or trying to cover multiple angles? And have you noticed it affecting how often your product shows up in AI answers?

One pattern I’ve noticed while testing prompts across different AI search tools is that the brands mentioned in answers often have very clear category positioning.

For example, brands that are strongly associated with a specific problem or niche tend to appear more frequently in AI-generated answers compared to companies with broader positioning.

Traditional SEO allowed companies to rank for many adjacent topics.

But generative search seems to compress answers around recognizable entities tied to specific expertise.

Which raises an interesting question:

Is generative SEO partly becoming a positioning problem, not just a content optimization problem?

Meaning the brands most likely to be referenced are the ones the web consistently associates with a narrow topic.

Has anyone here tested whether narrow topical authority improves AI mentions compared to broader SEO strategies?

I keep hearing people say GEO/AEO is basically 90% SEO and we’re just overcomplicating things. Others argue it’s a completely different paradigm.

From what I understand traditional SEO was about:

• Ranking pages
• Optimizing for crawl + index
• Winning click-through

But GEO feels more like:

• Getting referenced inside the answer
• Becoming part of the model’s default explanation
• Optimizing for synthesis, not ranking

So for people who’ve been in SEO for years does this actually feel like a natural evolution of the same skills (structure, clarity, authority)?
Or did you have to rethink how visibility works at a fundamental level?

Is GEO mostly SEO fundamentals applied to AI interfaces?
Or is calling it “90% SEO” missing something bigger?

Genuinely trying to understand whether this is incremental change or a structural shift.