u/YourEvilQueen26

This sounds obvious, but I think a lot of businesses still monitor Google rankings without checking the equivalent customer questions inside AI platforms.

Try asking:

"Who is the best [service] in [city]?"

Then try:

"Who would you recommend for [specific problem] in [city]?"

Then:

"What are some reliable [service] companies near [city]?"

The answers can be surprisingly different.

I've been experimenting with Signal AEO to look at visibility across ChatGPT, Gemini, and Perplexity rather than treating AI visibility as a single ranking:

https://signalaeo.com/

If you're doing local SEO, have you started adding AI recommendation checks to your normal reporting yet?

One of the biggest risks with outsourced development is paying a huge deposit and then spending months wondering what is actually being built.

I came across an interesting model from AppsTango where the first invoice comes after working code has already been delivered into the client's repository.

https://appstango.com/offer/pay-on-delivery

I haven't seen many agencies structure engagements this way.

For anyone who has hired a development agency before, would this materially change how comfortable you felt about outsourcing?

Or are team quality, references, and technical architecture still much more important than the payment structure?

Imagine five websites all make essentially the same factual claim.
Why might ChatGPT, Perplexity, Gemini, or another answer engine surface one source rather than another?
I suspect there's no single factor.
It may involve a combination of source authority, relevance to the exact question, how clearly the information is written, corroboration from other sources, freshness, entity relationships, and whether a specific passage can stand on its own.
That last part interests me especially.
A page can contain the correct answer while making that answer difficult to extract.
Another page might provide:
Question → direct answer → evidence → context
The second structure creates a much cleaner passage.
This is the idea behind Cited Logic: studying AI visibility at the citation and passage level instead of assuming traditional SEO signals explain everything.
One experiment I’d like to see conducted at scale is taking pages that already rank well, restructuring only their answer passages, and then tracking whether citation frequency changes.
Has anyone run something similar?

Traditional SEO gives us a familiar measurement model: keyword, ranking position, impressions, clicks, and conversions.

AI search is different.

A company might be recommended when someone asks, “What are the best companies for X?” but disappear when the prompt becomes, “Who would you trust for X?”

Because of that, I don’t think measuring a single AI “ranking” tells the whole story.

A better framework may be:

Prompt coverage: How many relevant customer questions mention the brand?

Appearance rate: How consistently does the brand appear when those questions are tested repeatedly?

Platform coverage: Does the company appear across ChatGPT, Gemini, and Perplexity, or only one platform?

Recommendation context: Is the brand simply mentioned, or actually recommended as an option?

Source/citation coverage: What websites and third-party sources appear to support the answer?

This is the approach I’ve been experimenting with through Signal AEO.

The interesting part isn't just discovering whether a business appears. It's discovering the conditions under which it appears or disappears.

I think that distinction will become increasingly important as AEO develops.

How are other marketers measuring this right now?

I've been looking into app development companies recently, and I'm realizing that comparing portfolios doesn't tell you nearly as much as I expected.

Two agencies can both show polished apps, but that doesn't tell you much about what happens behind the scenes. I'm more interested in things like:

* Do they challenge a bad product idea before development starts?
* How accurately do they estimate the budget and timeline?
* Do they actually think about scalability?
* What happens after the first version launches?
* Can they handle both the technical and product side?
* How are they using AI without just adding "AI development" to their marketing?

For anyone who's hired an app or software development company before, **what ended up being the biggest indicator that you'd chosen the right team?

Something I’ve been testing lately:

Take two articles answering essentially the same question.

Article A is longer, has better design, more internal links, and probably looks like the “better SEO page.”

Article B contains a very simple section:

Question

Direct 2–3 sentence answer.

Evidence/source.

Additional explanation.

When you start checking which information gets surfaced or cited in AI answers, Article B can become surprisingly interesting.

It made me wonder whether the unit we're optimizing is wrong.

SEO trained us to think about the page.

For AI citations, maybe we also need to think about the passage.

I’ve started using a simple test:

>

If it needs three paragraphs before it to make sense, it probably isn't a very clean extraction candidate.

That’s one of the things I want to explore more through Cited Logic: not just whether something gets cited, but what characteristics make information easy for an AI system to retrieve, understand, and reference.

Has anyone tested passage structure specifically? I'd be interested in examples where restructuring content changed AI citations without a major change in traditional rankings.

I’ve been running the same business through different AI search prompts, and I’m starting to think the idea of a single “AI ranking” is misleading.

Take a local company and test:

• “best company for X in Dallas”
• “reliable X company in Dallas”
• “who would you recommend for X in Dallas?”
• “X company for an emergency”
• “affordable X service near Dallas”

Same business. Same general service.

But ChatGPT, Gemini, and Perplexity can produce surprisingly different recommendations depending on the intent and wording.

What seems more useful to me is measuring appearance rate across a group of prompts.

That’s what I’ve been testing with Signal AEO: prompt-level visibility, platform differences, recommendation consistency, and which sources appear alongside the recommendation.

Instead of asking:

“What position do we rank?”

I’m starting to ask:

“Across 50 realistic ways a customer could ask for this service, how often are we actually part of the answer?”

That feels much closer to what AI visibility really means.

Curious if anyone else is measuring it this way. Have you found certain types of prompts to be significantly more stable than others?

Here's an AEO experiment I'd really like to see done properly.
Take one factual claim that appears on 20 different websites.
Same underlying information.
But the pages have completely different characteristics.
One has the original source.
One has stronger domain authority.
One was updated yesterday.
One explains the claim more clearly.
One uses structured data.
One has a named expert author.
One has the shortest, cleanest answer.
One has dozens of backlinks.
Then ask AI systems questions where that specific fact is needed.
Which page actually gets cited?
I've been thinking about this while working on Cited Logic because citation analysis gets complicated very quickly once multiple sources are saying essentially the same thing.
It's tempting to say "authority wins," but I'm not convinced it's that simple.
The interesting part would be repeating the experiment across ChatGPT, Perplexity and Gemini and seeing whether they consistently prefer the same source.
My guess is they wouldn't.
Has anyone seen research that isolates individual citation factors like this?
I'd love to compare results.

I've been thinking about something that doesn't seem to get discussed much in AEO.

Let's say a local business already has the basics:

• decent website
• Google Business Profile
• reviews
• service/location pages
• reasonable SEO

But ChatGPT or other AI tools still rarely mention it when someone asks for recommendations.

What happens if that business gradually starts getting discussed in more places?

Not backlinks necessarily.

I mean actual brand mentions in relevant conversations, articles, Q&A sites, industry discussions, local sites, etc.

My assumption used to be that the website itself would carry most of the weight.

Now I'm wondering whether AI systems need enough information outside the company's own site to become more confident about what the business actually does.

I've started watching this in Signal AEO by comparing AI visibility before and after businesses start picking up new mentions.

It's still too early for me to say there's a direct relationship, but it's something I want to test more systematically.

Has anyone here actually tracked this?

Would especially be interested if you've seen a previously invisible business suddenly start appearing in AI recommendations without a major change in its Google rankings.

One thing I’ve been noticing lately is how different AI recommendations can be from normal Google rankings.
A business can rank pretty well in search, have solid reviews, and have a decent website — but then barely appear when you ask ChatGPT, Gemini, or Perplexity for recommendations.
What makes it even more interesting is how much the wording of the question seems to matter.
For example:
“best roofing company in my area”
vs.
“who would you recommend for an emergency roof repair?”
vs.
“reliable roofer for replacing an old residential roof”
Those questions are related, but the businesses mentioned by AI can be completely different.
I’ve been looking at this through Signal AEO and it’s made me pay more attention to prompt-level visibility rather than treating AI recommendations like another version of Google rankings.
The part I’m still trying to understand is why certain businesses appear consistently.
Is it their website content? Reviews? Reddit and other third-party mentions? Local citations? Brand authority? Or some combination of all of them?
It feels like we’re still early enough with AEO that there’s a lot we don’t fully understand yet.
Has anyone here actually compared their Google rankings with how often their business gets recommended by AI?
Would be interested to hear what patterns you’re seeing.

I’ve been looking more closely at how AI tools choose sources, and one thing keeps standing out:

Having good content doesn't automatically mean you'll get cited.

Two websites can explain almost the exact same topic, but ChatGPT, Perplexity, or another AI search tool may repeatedly reference one while barely acknowledging the other.

It made me wonder what actually creates that difference.

Is it the authority of the domain?

How clearly the information is written?

The freshness of the content?

How easily a specific claim can be extracted?

Or does the AI simply have more confidence in one source because the same information is supported elsewhere?

This is one of the reasons I've become interested in Cited Logic — looking beyond traditional rankings and trying to understand the logic behind AI citations themselves.

Because knowing that your website isn't being cited is useful.

Understanding why another source is being cited instead is where things get interesting.

Has anyone here noticed certain websites consistently getting cited by AI even when they aren't necessarily the highest-ranking result on Google?

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I've been looking more closely at pages that get cited by AI answer engines.

One thing I'm increasingly interested in is how self-contained the actual answer is.

Imagine two pages make essentially the same point.

One buries the answer inside 1,500 words of content.

The other has a section with a clear heading, a direct answer, supporting evidence, and enough context for that passage to make sense on its own.

Which one is easier for an answer engine to retrieve and cite?

That's the part of AEO I think deserves more attention.

We're starting to explore this idea through Cited Logic — looking beyond rankings and focusing specifically on what makes content citation-friendly.

I'm curious whether anyone testing citations has noticed the same thing:

Do your most-cited pages also tend to have the clearest standalone answer sections?

Something I've been noticing while comparing local search results with AI recommendations:

A business can rank extremely well on Google and still barely appear when you ask ChatGPT, Gemini, or Perplexity for recommendations.

And sometimes a business sitting below them in traditional search gets mentioned instead.

That suggests we're dealing with two different visibility layers.

SEO: Can people find your business in search?

AEO: Do AI systems recognize and recommend your business when someone asks for an answer?

I've been using Signal AEO to track this specifically—running business queries across AI platforms and looking at how often a business actually appears.

I'm curious how other people here are measuring this.

Are you treating AI visibility as a separate metric from Google rankings yet?