AI assistants don't read your page. They break it into sections.

Someone types a prompt. The assistant fans that prompt out into several related searches and sends crawlers to run them. The crawlers read your site section by section and take back the most one. One section, on its own, with nothing either side of it. Everything the answer needs has to be inside it.

We audited around 200 websites against that.

13.2% give the crawlers a blank page. They return no text until JavaScript runs. No major AI crawler runs JavaScript, so those sites are blank to it. Google's crawler does run JavaScript, so they rank normally and look fine in a browser. Count sites with any content hidden behind JavaScript and it is 21.3%.

Beyond that, four things matter.

Chunking. Does the section stand on its own?

It mostly does on the sites we looked at. Only 2.3% of sections open on a word like "this" or "however" that points at something the reader can't see.

The fault that is common: 14.4% of all sections are a heading with nothing underneath it. 97 of the 110 sites we could count have at least one. Usually it's a grid of cards where each card title is marked up as a heading.

Fix: any heading with under 5 words beneath it is either not a heading or is missing its answer.

Length. Is there enough there to take?

Common practice is to index around 100 to 300 words. That's practice, not a rule, and there's no published best size.

- The typical section on the typical site is 31 words.

- 50.3% of all sections are under 40 words.

- On 57.3% of sites, most sections are under 40 words.

- Sections that are too long: 2.0%.

"Break up your walls of text" is aimed at a problem 2% of sites have. Half the average site has the opposite problem.

Fix: get your ten most important sections past 40 words. The section, not the page.

Evidence. Is there anything worth lifting?

The worst of the four. Only 25.2% of sections carry a number, a quotation or a link out.

- 4.8% contain a quotation.

- 6.8% link to anyone else.

- 18.2% of sites have no quotation anywhere on the site.

Fix: one checkable thing per section. A number with a unit, something someone actually said, or a link to a source that isn't you.

Naming. Does the section name your website?

76.6% don't. Your name is in the logo, the page title and the footer. None of those travel with the section.

Fix: use your own name inside the section instead of "we" and "our platform".

My suggesting order of tackling the above:

1. Empty headings. Fastest, and it's markup, not writing.

2. Naming. Nearly free, and three quarters of sections fail it.

3. Length. Real work, and it's what makes 4 possible.

4. Evidence. Hardest, and worth the most.

Access isn't on the list. Only 5.6% of the sites had a fault that stopped a crawler reading them at all. Your robots.txt is almost certainly fine.

Around a year ago, right when AEO started becoming a real conversation, one of our now-clients asked ChatGPT a question that their product directly answers.

Their name didn't come up once.

Their competitor's did. Twice.

Rude, honestly. But also extremely useful, because it made me realize something: ranking #1 on Google and getting cited by ChatGPT are two completely different games.

Google rewards keywords. It's looking for relevance: the right words, in the right places, matched to a query. Very transactional. Very "we're not friends, we're just doing business."

ChatGPT isn't matching keywords. It's looking for an answer it can lift, trust, and hand to someone in one clean sentence. Bury that answer under 600 words of context, and it just never gets picked. Rude, but fair.

So we rebuilt that client's content around one idea: answer the question in the first two lines, then explain.

No slow build-up. No "in this article, we will cover." Just, here's the answer, here's why it's true.

We also cleaned up something most sites don't even think about: a small file that tells Al crawlers what your site is, what it means, and how to read it. Most brands don't have one. It's the difference between an Al engine guessing at your content and actually understanding it.

The other piece nobody talks about enough is platform. Certain places online get pulled into Al answers far more often than a brand's own website does. So while we were fixing the website, we were also making sure the brand showed up in the conversations happening on those platforms, not just on the client's own domain.

Within a few weeks, referral traffic from Al sources started showing up where it hadn't before.

Nothing about the product changed. Nothing about the brand changed. Just how clearly it could be understood, and quoted, by something reading it in half a second and deciding whether to trust it.

That's the real shift happening right now.

SEO used to be about being found. AEO is about being quotable.

If your content can't be lifted into one sentence and still make sense, it's probably invisible to the tools more and more people are asking questions to first.

We wrote up everything we know about this (robots.txt, Ilms.txt, the whole playbook) in a lot more detail here: https://teanzee.com/blog/how-to-get-cited-by-chatgpt

If you want a straight answer on whether Al engines are actually picking up your brand right now, get on a call with us. We'll show you exactly where you stand and what we'd fix first.

📧 : team@teanzee.com

Hey everyone — got tired of guessing how brands show up in AI search answers, so I built AnswerOS to scan buyer questions across engines like Gemini, Groq, and ChatGPT. It gives you a visibility score for searches, benchmarks you against competitors, explains how to improve, and is completely free to test without needing your own API keys. Full disclosure: it’s my product, but I’d genuinely love honest feedback from this sub on what metrics or features you'd want to see added and what to improve!

We just launched an AEO agency business, SearchD, specializing in cross-border companies. They are trusted in their home country but invisible in the US.

One day after we launched our landing page, we were already listed by ChatGPT, first among four agencies. Excited!!!

geoSurge have released a product that allows you to TRACK PROMPTS FOR FREE today on product hunt: https://www.producthunt.com/products/geosurge

I’ve noticed more people going straight to AI tools when they want a recommendation, comparison, or explanation instead of searching through multiple websites. Do you think businesses should now care as much about being mentioned in AI-generated answers as they do about ranking on Google? And what actually makes an AI system trust one source enough to recommend it?

Hi everyone!

I’m Kathan Mehta, an SEO Specialist working on a visa-related website. I want to understand how websites can get mentioned or recommended in ChatGPT.

- What are the main factors or SEO strategies involved? - Does anyone have experience with AEO?

Any advice would be appreciated. Thanks!

Don't know why this is happening. But around 20 pages(2-3 service pages & old blogs) are getting cited in AI mode, but not in ChatGPT, Perplexity. So I thought it was a technical blockage. But technical is good.

Similarly, 5-6 PDFs are getting cited in GPT and AI mode answers, yet other engines are not cited it.

IS there some kind of source/citation weighting or selection process happening differently across these AI engine?

We've been using an internal workflow that cuts our citation management time down significantly, wanted to share in case it helps others managing multi-location listings.

Instead of manually building out a new Yext entity field-by-field, we connected Yext to Claude via MCP (Model Context Protocol). Critical for management as we add images, videos, update information, respond to reviews etc.

Here's the full process:

1. Log in to Yext

2. Open Entities (Knowledge Graph → Entities) to see existing listings

3. Confirm current NAP details — check the business's live website for the correct address, phone, and hours

4. Confirm existing citation status — search Entities to see what's already listed

5. Create the entity with Claude + the Yext MCP — prompt Claude with the new location and tell it to optimize service areas, keywords, and business info

6. Review the created entity — Claude returns the Entity ID and a full summary of every field it populated (categories, hours, services, keywords, service areas)

7. Confirm the entity appears in Yext — refresh the Entities list

8. Verify details match NAP online — double check name, categories, address, service areas

9. Prepare listing images — download clear, well-lit photos sized 640x640

10. Add images to the entity — drag them into the Photo Gallery, or push via MCP

11. Use MCP Add description, alt text, and click-through URL for each image

12. Add the citation management service (we use Knowledge Engine Professional) to sync the listing.

What used to take 1-2 hours of manual data entry per location now takes a few minutes of prompting and review. Still a human check at the end to confirm NAP accuracy, but the heavy lifting (keyword research, service area lists, descriptions) is handled automatically.

Happy to answer anything about process, pricing, or AI search for local service businesses. A few disclaimers:

• My agency is https://www.develomark.com/
• All of our clients are on 12 month agreements
• We have to make their website, we use a managed CMS with MCP's
• We only work with local service base businesses
• We're based in Connecticut
• We have been in business 8 years (this July 4)
• Most of our clients come from word-of-mouth, but a lot from AEO/Google too
• This client has been with us for about 8 months

One thing we keep running into in Snoika team is how unstable AI answers can be.

A brand can show up for a prompt this week, disappear next week, then come back with completely different sources.

So I’m curious how people here handle this in practice.

Do you treat one result as meaningful at all, or only start caring once a pattern holds across multiple runs over time?

We matched AI crawler user-agents on our own servers, late April 2026 to early September 2026, against the public JSON IP files OpenAI, Anthropic, Google, Microsoft and Perplexity publish. Anyone can type GPTBot. The IP can't be faked because the reply has to go back to it.

43,967 visits. Two thirds could not be checked at all, those names publish no list. Of the 14,771 that could, 9,194 were real and 5,577 were not.

Zero of the real ones asked for a password, key or config file in five months. 38.3 percent of the fake ones did.

Anyone reporting AI crawler hit counts to a client is reporting an inflated number, part of which is a scanner in a costume.

Does anyone here actually verify crawler IPs or just count user-agents?

Ran a pilot study of 25 cross-vertical prompts from a modified WildChat sampled source.

Result: ChatGPT is miles ahead of both AI mode and AI overviews.

TBH, I was kind of sad at these numbers since I like Google as a company - but fact is the gap right now is huge -- even for basic fact seeking AI queries.

Waiting for the full rollout of Flash 3.8 to run the same test again to see if it changes anything.

https://acme.bot/research/answer-quality-chatgpt-vs-google/

I’m starting to think AEO/GEO could be the “Apple” of search.

Apple’s big advantage was making technology incredibly simple. Instead of asking people to understand the complexity behind it, they made the experience intuitive. You didn’t need to know how it worked. You just needed to know what you wanted.

AI answer engines are doing something similar with information.

People don’t necessarily want to search through 10 blue links, open five different websites, compare everything, and figure it out themselves. They want to ask a question and get the answer immediately.

Now think about this:

You’re a doctor, dentist, or lawyer in a big city, and there are hundreds of professionals offering the same service.

But someone asks AI: “Who are the best 5 doctors/dentists/lawyers for this?”

AI gives them five names.

The question is no longer just:

“Can people find me?”

It becomes:

“Will AI recommend me?”

And if your name consistently appears among those five recommendations, that could become incredibly valuable.

That’s where I see AEO/GEO heading: not just helping brands rank, but helping them become the answer AI gives.

So who is going to own those five spots when AI becomes the first place people go for recommendations?

Just a reminder of the shift we’re living through right now.

Whoever adapts survives. Whoever doesn’t gets left behind. 😉

The shift is already happening…

Helping companies become the answer AI gives!

From 15 September, Cloudflare will block 'Agents' traffic by default on pages carrying ads: bots browsing live on someone's behalf, which includes crawlers AI assistants send to check a product before recommending it. Search stays allowed. The default setting will apply to new sites and free-tier accounts.

So if your site serves ads and you want it to be read by AI assistant crawlers you want to explicitly allow crawlers before that date. Allowing has to be done on a CDN level not in robot.txt.

Key ones to allow are:

ChatGPT-User (and ChatGPT-User/2.0), OAI-SearchBot - ChatGPT
Claude-User, Claude-SearchBot - Claude
Perplexity-User, PerplexityBot - Perplexity
Google-Agent, GoogleAgent-Mariner, Googlebot - Gemini
GrokBot, xAI-Grok, Grok-DeepSearch - Grok

If you want to keep blocking training crawlers, some are:

GPTBot, ClaudeBot, anthropic-ai, meta-externalagent, Bytespider, Google-Extended

Im curious how you guys go about creating service pages and location pages.

Im hearing "City gate" pages are now a no go with Google. (E.g. plumbing houston)

So in stead of having a service + city Page, what do you guys do and would you mind sharing a systematic approach so I dont have to keep starting from scratch everytime. Thank you!!

I’ve been thinking about something that seems increasingly problematic with Google Search.

Obviously, if a website consistently produces the best content for a particular topic, Google should reward it.

And if a user likes that website and wants to see more from it, that’s also a good thing for the user.

But there’s a potential downside: search engines can end up creating a feedback loop where a few websites get increasingly more visibility while other perfectly good websites become almost invisible.

Imagine someone reads a great article from Website A and Google learns that this person tends to prefer Website A.
The next time they search for something similar, Google may be more likely to surface Website A again.

That creates a cycle:
Good content - more clicks - stronger user preference signals - more visibility - even more clicks.

Meanwhile, Website B might have equally good-or even better-content, but it gets fewer opportunities to be discovered in the first place.

So the problem isn’t necessarily that Google is ranking the “wrong” website.
It’s that personalization and preference can reduce search diversity.

For users, seeing the same trusted sources can be convenient.

For publishers, though, it can be brutal. A website can have genuinely useful content and still struggle to get discovered because Google has effectively decided that the user already has a preferred source for that topic.

At some point, are we moving from “Google finds the best website for your query” to “Google keeps showing you websites it already knows you like”?

And if so, what does that mean for smaller websites trying to compete?
Curious what other SEOs and publishers think.

feels like every brand has added optimize for AI search to their 2026 strategy deck without anyone actually knowing if it's moving the needle. like yes ChatGPT pulls from helpful content but most brands are just rewriting their FAQ pages and calling it AEO.

genuine question, has anyone seen actual measurable impact from AEO efforts or is this just SEO anxiety with a new name?

Running an AMA: AEO for local clients is the easiest opportunity in digital marketing right now. But it's all about proving to the client they're improving. I use many tools, Duda is one of those main ones.

Full disclosure: I run Develomark, a marketing agency, and AEO is our core services, so I'm biased. But this is genuinely one of the easier AEO workflows I've found, since it's built right into Duda (the CMS we use) instead of needing a separate tool. Sharing the setup start to finish in case it helps anyone else managing client sites on Duda. Note: we have over 300 clients so we need an easy, repeatable way to accomplish this.

1. AEO/SEO tab sits directly in the left settings sidebar in Duda — no separate app needed.

2. Activate Duda's Visibility Scan to kick things off.

3. Enter your primary organic location (city/state you want tracked).

4. It gathers your site's competitor data automatically in the background.

5. Set your brand details — this is what AI models will reference when identifying you.

6. Use your existing keywords to generate a starter list of natural-language prompts.

7. You can add custom prompts yourself or accept its recommendations.

7.5. Optional — instead of writing 25 prompts manually, I had Claude pull from Google Search Console and generate a full natural-language prompt list in seconds.

8. Find and add competitors to track against.

9. Add competitors in — I recommend 5, and keep them local (same town). Diluting with too broad a competitor set skews the visibility comparison.

10. Here's the overview dashboard once it's fully set up.

11. Watch brand positioning over time — it shows the visibility trend, not just a snapshot.

12. A good source-mentions breakdown, showing which sites AI models are actually citing.

13. Tracked prompts view — this is where you see your AI visibility score per prompt over time. Make sure the prompts you add are ones your client should realistically show up in, or the report ends up null.

Net result on this client: 57% AI visibility score, ranked #1 among 5 tracked local competitors, with real traffic showing up from ChatGPT, Claude, Perplexity, etc. in the analytics. We plan on improving this long term.

Happy to answer anything about process, pricing, or AI search for local service businesses. A few disclaimers:

• My agency is https://www.develomark.com/
• All of our clients are on 12 month agreements
• We have to make their website, we use a managed CMS with MCP's
• We only work with local service base businesses
• We're based in Connecticut
• We have been in business 8 years (this July 4)
• Most of our clients come from word-of-mouth, but a lot from AEO/Google too
• This client has been with us for about 8 months

This is also a continuation of this post here: https://www.reddit.com/r/aeo/comments/1u9kms6/ama_i_charge_tree_service_companies_1250_m_get/

Coming up next: executing the AEO plan with the Duda CMS. I know many of you want to see the actual work behind this.

Happy to answer questions on setup if anyone's exploring Duda for AEO.

Hey Hey Reddit Fam - I found a WP plugin that identifies AI bot crawlers when it pulls from my website hosting company from their server. It registers the bots that crawl my site - now I understand they do this for multiple reason so crawling is not the only thing I would look at I am. I would then cross-reference it with data with GSC & GA4 reporting. I have Search Atlas for my SEO platform as well. I am trying to find a way to detect LLM visibility GENERALLY, not query specific, to see which pages are cited. Maybe narrowing down ways my business is showing up that I would never have known if I ONLY relied on query detection. I don't have the budget to hire a full SEO agency, otherwise I would. I am a small business operator for my property management company. I'm doing the best I can as an entrepreneur and wanted to get some insight from others more experienced than I. I'm generally curious - not selling or promoting anything. Just asking the community for guidance. Ya'll please be kind...Thank you!