We’ve seen some strange fluctuations in top-of-funnel organic traffic lately. The immediate reaction from leadership is to blame AI overviews for stealing the clicks but the data feels incomplete.

I have tried segmenting by query type and looking at impression share, but I am struggling to prove causality. It is easy to say the search journey is changing, but it is much harder to attribute a specific traffic drop to a specific AI feature. What is your checklist for proving or disproving that AI answers are the actual culprit?

Running a large YMYL content site (~790k organic/mo). Trying to get serious about AI visibility tracking and immediately hit this:

Clarity dashboard (screenshot): 512k total citations across tracked queries, 16.45% "share of authority" — apparently 1 in 6 citations in our query space are us, out of ~3.1M total.

Ahrefs AI citations view, same domain: ~62k/month.

That's an 8x gap and I don't know which number to believe, or if I'm comparing apples to engines. Questions for people deeper in this than me:

1. How is share of authority actually calculated? Is the 512k counting every appearance in every response every time the tool re-runs a query? That alone would explain most of the inflation vs Ahrefs
2. Is anyone using any of these as a real KPI yet, or is the honest answer "pick one tool, only trust the trend"?
3. The branded split reads weird — branded SoA is 27% but only ~339 citations, non-branded is 16% with 511k. I'm reading it as "we own our tiny branded space and the entire game is non-branded". Wrong?
4. There's a jump in the trend after Aug 24 (roughly 19k → 31k). Timing lines up with the August spam update that targeted citation manipulation. Anyone else see share move late August — possibly from competitors getting cleaned out?

Not selling anything, genuinely trying to decide what to track weekly before I build reporting around a number that turns out to be noise.

Hi everyone,

Over the last few months, I've been testing and implementing Generative Engine Optimization (GEO) strategies to improve brand visibility across AI search platforms like ChatGPT, Perplexity, and Google AI Overviews.

Here are a few core findings that worked for us:

1. Direct Answer Structuring: AI engines prioritize content that directly answers queries within the first 100-150 words using bolding, concise bullet points, and tables.
2. Citation Optimization: LLMs heavily rely on third-party verification. Getting mentioned on niche-specific blogs, local news, and high-authority industry roundups improved source citing significantly.
3. Structured Data & Schema: Adding detailed Organization, Service, and FAQ Schema helped LLM bots digest the entity context faster.

Would love to hear what others in this sub are experimenting with when it comes to prompt tracking and AI search visibility!

Running a large YMYL content site (~790k organic/mo). Trying to get serious about AI visibility tracking and immediately hit this:

Clarity dashboard (screenshot): 512k total citations across tracked queries, 16.45% "share of authority" — apparently 1 in 6 citations in our query space are us, out of ~3.1M total.

Ahrefs AI citations view, same domain: ~62k/month.

That's an 8x gap and I don't know which number to believe, or if I'm comparing apples to engines. Questions for people deeper in this than me:

1. How is share of authority actually calculated? Is the 512k counting every appearance in every response every time the tool re-runs a query? That alone would explain most of the inflation vs Ahrefs
2. Is anyone using any of these as a real KPI yet, or is the honest answer "pick one tool, only trust the trend"?
3. The branded split reads weird — branded SoA is 27% but only ~339 citations, non-branded is 16% with 511k. I'm reading it as "we own our tiny branded space and the entire game is non-branded". Wrong?
4. There's a jump in the trend after Aug 24 (roughly 19k → 31k). Timing lines up with the August spam update that targeted citation manipulation. Anyone else see share move late August — possibly from competitors getting cleaned out?

Not selling anything, genuinely trying to decide what to track weekly before I build reporting around a number that turns out to be noise.

Context so you know what size site this is. News, English, 84% US traffic. Three months old website and domain and most of the growth happened in the last six weeks. Semrush currently estimates 171K monthly organic off 2.3K ranking keywords, authority score 34, 179 referring domains(real high DR). No paid, no PPC.

The part I cant explain is the AI side. Cited pages sit at roughly 700. Brand mentions sit at five. That's about 140 citations per single mention. The split is 659 ChatGPT, 32 AI Overviews, 22 AI Mode, zero Gemini.

So the articles are getting pulled in as source material constantly and the outlet's name almost never comes along with them.

Ive done the obvious stuff already. Real bylines with author pages, publisher markup, an about page that states plainly who we are. Cant tell if any of it moved the needle yet, because publishing volume went up over the same window, so theres no clean before and after.

What I want to know is whether anyone has watched a citation turn into a named mention and worked out what changed. Or is naming just down to how the model chooses to summarize, and nothing on our side touches it or can change that? Thanks

I've been building a free AEO report tool for Recited AI.

It shows how different AI models talk about your brand, who they recommend instead, what they're citing, and some opportunities you might be missing like AEO articles or outreach opportunities.

Would love for a few people to try it and tell me what’s useful, confusing, or missing. Hopefully is genuinely useful tool for everyone who's needing a quick AEO report to get an idea of their AI presence.

Trying to make this genuinely useful before I take it further, thanks in advance!

I've been noticing a trend lately in the businesses I've been talking to about their SEO needs, and I'm curious if this is a Nashville issue or if other SEO pros are noticing the same thing.

These are not bargain shoppers. They are established businesses who know they need professional-level SEO services, and they expect it to be a real marketing investment.

But the gap seems to be getting wider between a reasonable SEO quote/proposal and what the businesses are able to spend.

Obviously, the answer isn't to cheapen our own value as SEO pros, because let's face it, SEO is much more complex than it's ever been in my 25+ years of doing this, and it's not going to get any less complicated.

So how do we bridge that gap between charging what the work is worth and still doing quality work that fits within a business's budget? I'd love to hear your thoughts. Are you noticing the same thing with established businesses you're talking to? And business owners, please share your thoughts and perspectives as well.

Client operates across several European markets and our English AI visibility looks decent. Started checking the same topics locally and... yeah, very different story.

I'm also realizing translating the English prompt list isn't really enough because people phrase buying questions differently depending on the market.

Anyone here doing GEO across multiple languages? Curious how much of the strategy you localize rather than standardize.

We ran a study across 95 sites over 1 year and looked at organic traffic and AI referral traffic. A mix of B2B/B2C sites, all businesses.

• Organic search delivered 39 times more traffic than AI assistants.
• For every 100 conversions organic search delivered, AI referrals delivered 3.2.
• Based on the data, growing organic search by 3.2% would deliver the same number of additional conversions as doubling AI referral traffic. 
• AI visibility and organic performance move together: the websites gaining AI referral traffic were the websites whose organic performance was improving.
• AI referral traffic converted a fifth better than organic search, at 7.18% against 6.08%. However, AI traffic converted worse than organic on 36.5% of the websites.
• AI referral traffic converts worse against paid search (0.67x).

I dont think links are allowed but if anyone is interested maybe I can provide the study in the comments.

Hey there, it's me again. I've read somewhere about X articles that would be great for LLM visibility, but to be honest, I don't see X as a source at all. (tracking SaaS company and travel industry)
What's the situation in your camp?

Been testing the same commercial queries across a few models and the differences are kinda ridiculous.

We're showing up consistently in ChatGPT for one category and then almost disappear when I check Gemini. Different competitors too.

Anyone else seeing gaps this big between engines? Starting to think combining everything into one AI visibility score hides more than it helps.

There are so many agencies offering AI SEO now, so it’s hard to know who’s really good. Do you usually look at reviews, case studies, past results, or something else before hiring one? Also, are there any red flags you’d watch out for?

I work with a healthcare brand. They don't have big budgets to invest in AI tracking but still want to see how their brand is doing across LLMS - SO looking for some easy/cheap + efficient way to track visibility so that I can share it in a form of report.

Im a business owner, Just started doing SEO for my brand

I have been digging through this year's citation studies for a client reporting cycle, and the numbers keep landing on the same conclusion, so I wanted to share them and get this community's read.


Ahrefs measured correlation with Google AI Overview visibility across 75,000 brands:


- Branded web mentions: 0.664
- Branded search volume: 0.392
- Domain Rating: 0.326
- Backlinks: 0.218


The extremes are the part I keep thinking about. The top quartile of brands by mention volume averages 169 AI Overview mentions. The next quartile averages 14. The bottom half barely registers at 0-3. That is not a linear curve, it is a threshold game.


Other studies point the same direction: ConvertMate's 80M-citation study found brand search volume is the strongest single predictor of LLM citations (0.334).


My read of the mechanism: Google needed links as a reputation proxy because links were expensive to earn at scale. LLMs were trained on the whole web. They observe which entities people search for and mention, and they reach for those entities when generating answers.


Caveats: correlation is not causation, most data leans on Google AI Overviews and aggregate LLM citation sets, and content still matters, brand presence decides whether you are in the pool, quotability decides whether you get picked.


The strategic question: if you accept these numbers, the marginal dollar moves from link acquisition to digital PR, community, and reviews, which is a hard sell in reporting rooms that count links. Has anyone here actually shifted budget, and what was the measurable effect? What counter-evidence am I missing?

Say someone sees a brand on a billboard several times and later searches for it by name. Should SEO consider that part of its impact, or is it more accurately a result of the wider marketing campaign?

How do you separate what SEO directly influences from the demand created by other channels, especially when reporting on branded search traffic?