We can see lot of SAAS brands are adding tons of comparison pages on their own website. The comparison is between each of their competitor and themselves. And we all know the obvious winner here. Some of them are even putting down competitor on every metric of comparison. Will not this activity hurt in the long run when AI gets smarter with identifying such pages.

Hi r/aeo,

I've been tracking AI citations for my site (about 2 months old) via Bing Webmaster Tools, and the data has been all over the place.

Over the past 7 days:

- Total citations: ~865

- Avg. cited pages: ~22

- But the daily numbers swing a lot — citations dropped significantly around May 16, then spiked on May 17, then leveled off

Some questions I can't figure out:

1. Is this kind of volatility normal for a newer site, or is it a red flag?

2. Does page count matter a lot — should I be publishing more content to stabilize citations?

3. Any specific things you've done to make your content more "citation-worthy" for AI like Copilot?

I'm mainly being cited via Microsoft Copilots and Partners. Would love to hear from anyone who's been through the early-stage AEO journey. Thanks!

Curious how people here are handling reruns / sampling methodology for GEO / AI visibility tracking.

When you measure brand visibility in ChatGPT, Perplexity, Gemini, Claude etc.:

- how many prompt variants are you using per intent cluster?

- how many reruns per prompt?

- how often do you refresh measurements (daily, weekly, realtime)?

Right now I’m testing:

- ~15 prompt variants

- 3 reruns

- daily/weekly tracking

- limited reruns

But I’m noticing pretty high variance between sessions and models, especially in ChatGPT and Perplexity.

Trying to figure out what people consider statistically “good enough” before drawing conclusions for clients.

Feels like a lot of GEO tooling is still using methodologies that are way too small to be reliable.

Has anyone here had a strategy that really worked for getting a brand mentioned more often in ChatGPT, Perplexity, Gemini, Claude, or AI Overviews?

Not theory, actual actions + results.

What did you do?
How did you track it?
How long did it take?

Feels like SEO is slowly changing into something much bigger now that AI search and answer engines are becoming mainstream.

It’s no longer only about ranking pages on Google, but also about whether your brand, content, and expertise are structured well enough for AI systems to actually reference and trust.

Companies with clear authority, consistent educational content, and strong digital credibility may end up having a huge advantage in the next few years.

Seeing a lot of debate around this lately.

Some people are scaling thousands of pages with programmatic SEO, while others say AI search is rewarding real expert-driven content more than ever.

From what I’m seeing:

• Programmatic SEO still works for structured intent at scale
• But expert content seems to build more trust, mentions, shares, and AI visibility long term

Feels like thin scaled pages are getting easier to ignore now unless the site already has authority.

What’s actually working for you in 2026?

• Programmatic SEO
• Expert content
• Or a mix of both?

Linear.app AEO audit

are llm engines really drawing from youtube video transcripts this heavily when it comes to product recommendations sometimes?

i guess maybe since general user prompts also overlap quite heavily with the title of these '{saas product} alternatives" videos and authority is easier to gauge from youtube accounts as opposed to reddit?

could be the case for just this report on Linear but interesting that almost 50% of the cited urls were youtube

https://preview.redd.it/k03kdhr5n92h1.png?width=747&format=png&auto=webp&s=62492eddd1a1318f5db9364eb42a04295d79ee70

Hello everyone! My name is Garry Callis Jr., and I'm the Community Manager of a website known as Discover AIO. DAIO is all about teaching marketers of all business backgrounds how AI SEO/AEO/GEO can work for you and your business. As you can see from the title, I want to talk to you all about the Buyer's Journey and how AI has heavily influenced the process and why as marketers should be thinking about the content we create and post.

Just a visual of the crossroads of the Buyer's Journey. Yes, generated with Gemini. Full disclosure there.

There are 3 stages to the Buyer's Journey.

1. Awareness
2. Consideration
3. Decision

Or at least, that's what we know traditionally. AI has taken the second stage, Consideration, which is, in my opinion the most important one, and has hijacked it. When someone enters a query into Google, ChatGPT, Perplexity, Claude, or their LLM of choice, they're already aware of an issue and are considering ways to fix it. AI now has something to look for, and inside of a few seconds, already has an answer for the prospect in question. So we have to make sure that in the spirit of Answer Engine Optimization, that we are considered the answer in search. So think about the content that exists about you and your brand, and how it can influence the decision of a prospective buyer. This makes the decision stage so much easier, because you've provided the proper content for AI to find you.

These are the bones of an article I'll be publishing on discoveraio.com pretty soon, but I wanted to get some dialogue going to see what everyone feels about this.

We're gonna be doing a webinar on the 4th of June, 2026 at 10am EST, and if you're interested in joining, shoot me a DM. We'd love to have you.
Discover AIO isn't just a learning platform, it's a community hub where you can post your own articles and connect with other marketers in your field or different fields.
Head to discoveraio.com/articles and see what else we have.
Thank you to r/aeo for the opportunity to post.

\*Is anyone else tracking AI visibility separately from traditional SEO?\*

\*I've noticed my clients rank well on Google but barely get mentioned when someone asks ChatGPT the same question. Started monitoring this manually and the gap is significant.\*

\*How are you handling AI search visibility for your clients? Any tools or processes you've built?\*

For years, SEO audits were treated like the universal fix for organic growth.

Traffic dropping? Run an audit.

Pages not ranking? Run an audit.

Technical issues piling up? Run an audit.

And to be fair, audits still matter. You absolutely should know if your site is slow, broken, hard to crawl, or full of duplicate pages.

But here’s the problem:

A clean SEO audit doesn’t guarantee visibility anymore.

Search has changed.

People don’t just search on Google and click ten blue links now. They ask ChatGPT for recommendations. They use Gemini summaries. They trust AI over individual websites more often than they probably should. Search results themselves are becoming answer engines.

Which means the old playbook — fix metadata, improve Core Web Vitals, add internal links, publish blogs — isn’t enough by itself.

You can technically “pass” every SEO audit and still become invisible.

That’s the uncomfortable reality a lot of brands are running into right now.

The Internet Is Moving From Ranking Pages to Referencing Sources

Traditional SEO was built around rankings.

You created a page. Google indexed it. You tried to outrank competitors. Users clicked your link.

Simple.

But AI systems work differently.

They don’t just rank pages. They synthesize information. They summarize. They compare. They cite. They recommend.

And increasingly, they answer the user without sending traffic anywhere.

That changes the entire visibility model.

Now the question isn’t only:

“Do we rank?”

It’s also:

“Are we being used as a trusted source?”

Those are two very different problems.

A traditional audit can tell you if your sitemap is broken.

It usually cannot tell you:

• whether AI systems understand your brand
• whether your content is consistently referenced
• whether your product positioning is clear to LLMs
• whether competitors dominate AI-generated answers
• whether your expertise is machine-readable
• whether your content structure actually survives summarization

That’s where a lot of companies are stuck.

They’re optimizing for search engines from 2018 while user behavior is already somewhere else.

Most SEO Audits Are Backward-Looking

Another issue: audits are mostly diagnostic.

They tell you what’s broken.

They rarely tell you whether your visibility strategy matches how discovery works today.

A typical audit focuses on things like:

• crawlability
• indexing
• metadata
• site speed
• schema
• redirects
• keyword usage
• backlinks

All important.

But none of those alone explain why some brands suddenly show up everywhere in AI-generated answers while others completely disappear.

Because AI visibility isn’t just technical.

It’s contextual.

AI systems look for signals of credibility, consistency, topical depth, citations, sentiment, and entity relationships across the web.

That’s a much broader ecosystem than what most audits measure.

For example:

Two companies may have equally optimized websites.

But one company:

• gets mentioned in industry discussions
• publishes original research
• has founders appearing on podcasts
• is referenced by trusted publications
• has consistent positioning everywhere online
• owns a clearly defined category narrative

The other company only publishes SEO blog posts.

Guess which one AI systems are more likely to reference?

Visibility Is Becoming a Distribution Problem

This is the shift a lot of marketers haven’t fully internalized yet.

SEO used to reward optimization heavily.

Now visibility increasingly rewards distribution and authority.

In other words:

It’s not enough to create content. Your brand has to exist across the broader information graph.

That means:

• third-party mentions
• expert citations
• cross-platform consistency
• authoritative references
• strong brand associations
• original insights
• topical ownership

AI systems don’t only learn from your website. They learn from the internet.

That’s why some smaller companies suddenly punch above their weight.

They may not have the biggest domain authority. But they’ve become highly referenceable.

And referenceability is becoming one of the most valuable forms of discoverability online.

Technical SEO Still Matters..but not by itself

This doesn’t mean technical SEO is dead.

Far from it.

If your website is impossible to crawl, painfully slow, or structurally chaotic, you’re still creating problems for both search engines and AI systems.

Good technical foundations still matter.

But technical SEO is now the baseline. Not the competitive advantage.

That’s an important distinction.

Having a technically sound site today is similar to having a mobile-friendly site a few years ago.

It’s expected.

The brands winning attention are layering strategy on top of technical health:

• differentiated expertise
• opinionated content
• strong entities and brand associations
• original data
• ecosystem visibility
• multi-platform authority
• machine-readable structure
• clear semantic positioning

That combination is much harder to replicate than “fixing SEO errors.”

The Biggest Mistake: Treating SEO as a Department Instead of a Reputation Layer

This is probably the bigger strategic issue.

A lot of companies still treat SEO like a checklist handled by one team.

But modern discovery doesn’t work in silos anymore.

Your visibility is affected by:

• PR
• social content
• podcasts
• reviews
• founder presence
• documentation
• community discussions
• customer sentiment
• product positioning
• analyst mentions
• YouTube videos
• research reports
• Reddit conversations
• media citations

AI systems absorb all of this.

Which means discoverability is increasingly tied to overall digital reputation, not just website optimization.

That’s why some brands with mediocre SEO fundamentals still dominate attention.

They’ve built strong informational gravity.

The internet talks about them constantly.

AI systems notice that.

What Companies Should Actually Be Doing Now

If you’re still running SEO exactly the same way you did three or four years ago, this is probably the moment to expand the strategy.

A smarter visibility approach today looks more like this:

1. Keep Technical SEO Healthy

Yes, still do audits. Fix crawl issues. Improve performance. Clean up architecture.

Ignoring technical SEO is still a bad idea.

Just stop assuming it’s enough.

2. Build Clear Topical Authority

Own a category. Own a narrative. Own specific themes deeply.

Generic content is getting compressed into AI summaries faster than ever.

Strong expertise stands out more now.

3. Create Original Information

Original data, research, frameworks, opinions, benchmarks, and case studies matter more because AI systems value reference-worthy material.

If you only rewrite existing information, you become replaceable.

4. Increase Off-Site Presence

Visibility now extends beyond your domain.

Appear in:

• industry publications
• podcasts
• interviews
• communities
• newsletters
• video platforms
• discussion forums
• expert roundups

The broader your informational footprint, the stronger your authority signals become.

5. Think About Machine Readability

AI systems process structure differently than humans.

Clear formatting, semantic clarity, concise explanations, strong entity associations, and contextual consistency all matter.

Messy positioning confuses both humans and machines.

6. Measure More Than Rankings

Rankings still matter.

But they’re no longer the full picture.

Companies should also monitor:

• AI citations
• brand mentions
• visibility across answer engines
• sentiment
• entity recognition
• assisted discovery
• referral quality
• share of voice

The search landscape is becoming much more fragmented.

Your measurement systems need to reflect that.

The Real Shift

The biggest change happening right now isn’t really about SEO.

It’s about how information gets trusted.

Search engines used to primarily reward pages.

AI systems increasingly reward trusted entities, strong relationships between ideas, and broadly reinforced expertise.

That changes how brands need to think about visibility.

A site audit can still tell you whether your foundation is healthy.

But visibility today depends on something much bigger:

Whether the internet sees your brand as worth referencing.

And that’s not a problem you solve with metadata alone.

Hey, i've been working on an open source cli for understanding if you get cited in chatgpt vs your competitors. Wondering if there are any experts in the field who are interested to further build this out?

At first I went down the rabbit hole of “optimise for AI” videos and all that. Added FAQ schema everywhere, rewrote intros, tried all the “40-60 word answer block” tricks people keep posting about. Some of it helped a little. most of it felt like chasing ghosts tbh.

What actually helped us was the less fancy stuff..

We cleaned up pages so answers were easier to find. less fluff. more direct explanations. We updated old posts instead of pumping 50 AI blogs every week. Also noticed pages with actual opinions/examples got picked up more than generic “ultimate guide” stuff.

One weird thing tho Reddit mentions and community discussions matter WAY more now than i expected. Same with reviews and people casually mentioning your brand in comparisons/discussions. AI tools seem to trust that kinda stuff a lot. I worked with a small team from InBound Blogging on one SaaS project and they kept pushing this idea that AI visibility is basically “brand familiarity across the web” not just rankings. sounded kinda buzzwordy at first but after tracking prompts for awhile… i get it now. Also been testing some GEO stuff with a GEO focused team called Rubicly recently and the biggest takeaway for me was “SEO still matters first”

if your site is slow, confusing, thin, or has no authority… no AI optimisation trick is saving you. Feels like AI search just rewards sites that already explain things clearly and are talked about in enough places online.

Let me know what others are actually seeing tho because half the linkedin advice on this topic feels completely made up IMO.

I have been trying different content strategy and testing visibility on a few AI visibility / GEO tools lately and noticed something interesting

Most tools track:

- mentions

- citations

- prompts

- AI share of voice

But the brands showing up most in ChatGPT/Perplexity answers often aren’t the ones with the best SEO.

A lot of visibility seems influenced by:

- Reddit discussions - - comparison blogs

- review sites - repeated brand mentions across the web

I think AI visibility is more about brand presence and contextual mentions than traditional rankings alone.

What has been your experience so far?

My supervisor asked me to prepare an “AI SEO performance report” and compare where we were before vs where we are now. From the way he explained it, I’m pretty sure he actually means AEO / answer engine visibility rather than traditional SEO.

The problem is I’m not fully sure what metrics people are realistically tracking for this yet.

For people who track AI visibility: how many prompts do you usually track for one brand?

Is it 20–50 prompts, 100+ or much more?