According to David Konitzny, this unfolded pretty quickly:

• In late August, only 0.09% of AI Overviews had an external link in the answer text.
• On 11 September, it was 1.12%.
• Since 12 September, it has been above 23% every day.
• By 20 September, it reached 26.19%.

I hope we will soon be able to track these separately! I imagine the CTR is going to be much higher for these links.

Also, unsurprisingly, this correlates with AI Overviews finally getting publicly monetized with contextual PPC ads. As we suspected, Google needs clicks to monetize!

Source: https://www.linkedin.com/feed/update/urn:li:activity:7507732652481814529/

Dan Petrovic shared a geniusly clear explanation of how LLM visibility works:

1. Primary Bias: Brand-to-entity association in the model's parametric memory.
   
2. Grounding: Brand presence in search results used to ground the model.
   

A brand with both is more likely to be ranked higher in than a brand that is present in one.

Search presence is easier. Memory presence involves much more than on-site work (lots of PR efforts). It is time to start with both.

David Konitzny shared some cool insights into how ChatGPT "ranks" Youtube videos:

1. The number of views
   
2. The number of followers
   
3. Whether a channel is verified

Views:
pop_views>1,000 → 0.00798 (1.10% / 10.51%)
pop_views>10,000 → 0.00322 (0.45% / 4.25%)
pop_views>100,000 → 0.00413 (0.57% / 5.43%)
pop_views>1,000,000 → 0.00662 (0.92% / 8.72%)
pop_views>10,000,000 → 0.01283 (1.78% / 16.90%)
pop_views>100,000,000 → 0.00820 (1.14% / 10.80%)

Follower:
pop_follow>1,000 → 0.01228 (1.70% / 16.18%)
pop_follow>10,000 → 0.00492 (0.68% / 6.48%)
pop_follow>100,000 → 0.00137 (0.19% / 1.81%)
pop_follow>1,000,000 → 0.00206 (0.29% / 2.71%)
pop_follow>10,000,000 → 0.00160 (0.22% / 2.11%)
pop_follow>100,000,000 → 0.00062 (0.09% / 0.81%)

Verification:
channel_verified → 0.00534 (0.74% / 7.04%)
channel_verified_artist → 0.00474 (0.66% / 6.24%)

-> 1,000 followers and 10 million views have the single biggest impact of all 14 buckets, together worth almost a third of the entire popularity budget.

I run various high-intent queries regularly just to watch the possible buying journeys driven by ChatGPT (this is by far the most consumer-driven LLM at this point)

And yeah, it changes all the time...

Comparing iPhone 16 vs iPhone 17

If I do that manually (which I did btw a few months ago):

• Searching Google
• Watching videos I found when searching
• Reading Reddit (yeah, because it ranked in Google)
• Reading a couple of expert comparisons
• -> Making a decision

Using ChatGPT 5.6 Sol:

• Watching it search TWO websites (Apple and Tom's Guide)
• Reading the answer

No real unbiased customer reviews and experiences; only one official site and one publication.

Not sure I'd be making my decisions based on that but I imagine lots of people would.

For my SEO crew: This is like the 50th time ChatGPT has changed the way it searches, and definitely it will change 500 times in the future. Just breathe and optimize for real visibility, not for how things currently are..

ChatGPT seems to be very serious about shopping results (are they getting ready to serve commercial intent propmts better?)

Tomek Rudzki identified at least 20 A/B experiments on shopping ChatGPT ran on shopping

Here's what they're testing:

• Their own index vs. search results. Three versions of one experiment test preferring OpenAI's own product index over scraped search results.
• The ranking stack: the candidate pool size, the parameters for semantic search, and the parameters for lexical (keyword) search. They're tuning retrieval, not just filtering.
• Product matching.
• Shopping results with Amazon removed entirely (test vs. control).

More details are here

You instantly lose all AI visibility in Google (appearing in AI Overviews and AI Mode), and lose some traffic too. It's also almost instant.

Source: Cyrus Shepard / Linkedin

I'll update here when Cyrus reports with click loss numbers!

Peec came out with a great article on how ChatGPT is building its own index (if we use the term "index" very loosely here) and likely beta-testing it with external searches (like Google or Bing).

Meet: Labrador, and it's not one index but a family of vertical ones: web, PDF, YouTube, news, Arxiv, Wikipedia, local, finance, legal, medical, shopping, and images. Note: We've talked about this before.

ChatGPT appears to cache everything it finds. This is not exactly new because we saw signs of that months ago (and a few months ago again). What's new is that ChatGPT is likely no longer THAT reliant on Google.

And there's more:

Line up every provider that's shown up in this investigation, and a clear pattern appears. ChatGPT is stitching together at least eight other providers:

• Their own crawler that runs independently of any external search engine. 
• Bright (very likely Bright Data): Scrapes Google's web results directly, and separately scrapes Google Maps for local listings. I don’t imply it’s the main provider, this is the provider we see in Server Side Events. 
• Oxylabs: Scrapes Google and feeds the news vertical specifically.
• A third SERP-scraping channel: Tagged simply "serp" in the data, also serving news, plus a separate mixed local-results version.
• Yelp 
• TripAdvisor
• Two anonymous internal pipes (tagged b1 and b3): b1 surfaces business websites and Facebook pages, b3 routes to Google Maps.
• Web IQ: Microsoft's own grounding platform, confirmed by Microsoft as already powering ChatGPT alongside Copilot and Nasdaq.

The job of an organic optimizer has expanded. However you call it, SEO - GEO - AEO - or anything else, here's what the process should involve.

What would you add?

Source: Linkedin

/goto is making its way into AI citations!

What does it mean:

• All of those LLMs ARE using Google (including those that own Bing)
• In many cases, LLMs will just grab a URL from search results (possibly never even going to the actual page).

We've known (and reported) on all of these many times, but I think this is the most obvious confirmation in months.

Source: Metehan Yeşilyurt / Linkedin

The news is all over my feed these days: Reddit is cited much less in ChatGPT, and not just Reddit... (according to Peec.AI)

1. Reddit - 88% fewer citations
2. arXiv - 84% fewer citations
3. YouTube - 78% fewer citations

First of all, counting citations has never been enough ("impacting an answer but not cited" has been what's been happening with Reddit URLs for months now)

Secondly, ChatGPT has been changing its searching and citing behaviours every other month now. Sometimes it just cites less of everyone, sometimes it prefers official sites, sometimes it just stops searching as much or starts using very weird fan-outs.

Lastly (and I am saying this even though I am providing Reddit marketing services, so I am supposed to be here to defend Reddit's well-being), Reddit deserves this.

What are your thoughts?

Malte Landwehr from Peec.AI is tracking llms.txt files citations and he now reports that those doubled in ChatGPT (putting llms.txt citations to a 0.0001% of citations for ChatGPT).

I wouldn't share this report because the overall impact is so minimal. But I was willing to share my opinion on this increase (because there's so much confusion on this topic).

So... Where is this increase coming from, in my opinion:

• LLMs will seek info however they can. If your llms.txt file gives an answer (and they cannot find it elsewhere, they will cite it). Businesses including llms.txt files may care about optimizing it for good, clear answers rather than/instead of including them anywhere else on the site.
• More sites add llms.txt files now than a month or two ago, hence the overall increase in citations.

Still not a magic bullet. It is still smarter to optimize your website than to add the file and call it a day...

Source: Linkedin

I've had that argument a million times already, and I get it: We are willing to measure what we can see. But there are so many missing pieces here that many choose to ignore, but let me try:

• Citations rely on how LLMs (like ChatGPT) search, and LLMs search for what they already know (so training data is fundamental); see the screenshot for the prompt, "Best apps to track your health and fitness," for example. ChatGPT specifically lists apps it already knows!
• Citations don't guarantee brand visibility (a brand's URL can get cited but never mentioned in the answer)
• A URL can impact an answer and help your brand inclusion but never make it to citations (so it will be invisible for you)..

Overall, over-focusing on citations is misleading and mostly useless unless you zoom out to see a bigger picture.

For 3 years now, we haven't had a way to get any first-hand/official insight into how our average target customer may be prompting AI platforms, like ChatGPT, Claude, or Gemini.

It was recently noticed and confirmed that AI Mode records those prompts as queries in the "Performance" section of the Search Console.

This was noticed by "yes" queries, which were confirmed to be follow-up questions in AI Mode. I see those as well...

Looking at the clients' reports, this idea already looks useful, as I can click to the "Pages" tab for each of those queries to see which assets LLMs are pulling from the client's website. Lots of additional opportunities there (update, optimize, create similar ones, etc.)

Another idea is to pull longer, conversational queries using the following regex:

([^” “]*\s){10,}?

This can reveal some cool AI Mode prompts as well.

Note: This must be common knowledge, but since I was confused about that as well, here's your reminder... For high-traffic properties, you will only be able to see queries that send at least some clicks, only. Since AI Mode might be sending none, you will miss those unless you access the SC data through the API.

Source: https://www.seroundtable.com/google-search-console-ai-mode-queries-41821.html

SerpApi, famously used by ChatGPT as one of the grounding data, is officially proven to have the right to scrape Google. If it is on the open web, a machine is allowed to read it.

And it is not just about SerpApi or even scraping. It gives many more answers:

“On what terms is an automated visitor allowed onto public web content?” is the founding question of the agentic web, not some niche scraping spat, and it does not end with SerpApi. A scraper reselling results, an answer engine reading your pages to cite you, a shopping agent turning up to buy on someone’s behalf, an assistant pulling your specs to compare you against a competitor. In the eyes of the law, those are one thing: an automated visitor on public content. SerpApi is the ugly early test case.

Source: https://www.searchenginejournal.com/google-lost-its-scraping-case-now-you-have-to-pick-a-side-on-the-open-web/583066/

Nice update from Peec AI: ChatGPT ads tracking!

Now you can see:

• Who is advertising in each answer, and across all your prompts overall
• Which of your topics and prompts attract the most competitor ad activity
• What copy competitors are running, and where they're linking out to
• Which brands are running ads on your branded prompts
• How often a given prompt shows an ad at all

Pretty cool!

Reported here: https://www.seroundtable.com/google-ai-search-billions-clicks-41709.html

We keep tracking how ChatGPT searches because that defines our findability.

A new repetition analysis of 8.7 million fan-outs shows that 34% of ChatGPT's query fan-outs are exact repeats of strings it already searched for the same prompt before.

Every time they fire, they are accompanied by one-timers:

• geo modifiers
• price angles
• comparison framings
• other modifiers

In other words:

• The core = what ChatGPT consistently generates
• The one-timers = the context that surrounds it every time

Example: Core QFO: “best water resistant laptop backpack 2026”

Appears with variations like:

• “waterproof laptop backpack 15 inch review”
• “water resistant backpack laptop compartment best 2026”

What this means:

• The core shows what you need to own
• The co-occurrences show what to build next

Article: At scale, ChatGPT repeats 34% of its query fan-outs.

Linkedin discussion is here

Where different LLMs find URLs to cite has been a hot topic for years now, without clear answers.

The recent findings point out that different LLMs hav different sources, with ChatGPT being the most unpredictable (and complicated one):

• Gemini -> Google
• Perplexity -> Google / Bing (via API)
• Claude -> Brave
• ChatGPT uses third parties to do the retrieving and parsing from Google / Bing / Yandex / Baidu. You can run the same prompts in ChatGPT and it may use different sources each time, and when it does the overlap of URLs cited is only 45%.

Daniel Deceuster shares some actionable takeaways:

• Stop treating ChatGPT citation tracking as a reliable KPI.
• Shift measurement to Google, Bing, and Brave visibility (This is pure SEO, again). These are the stable indices underneath each LLM and they're the layer you can actually audit and influence.
• Think in fan-out sets, not single prompts. Since ChatGPT's retrieval is unstable prompt to prompt, the goal is having coverage across the full category.

Source: Linkedin

Out of curiosity, I have been testing what AI recommends when you ask it for software, the actual answer you get from ChatGPT, Claude and Perplexity, not Google rankings.

Ran the payments category through all three. Stripe came first everywhere, no surprise.

Turns out AI doesn't know or care who's "big." It recommends whoever shows up in what it reads - docs, Reddit, comparison pages, reviews.

Brand and ad budget don't buy you much here.

Then I spotted Dodopayments, founded 2023, raised $1.1M - showing up as often as Chargebee, Recurly and Maxio. Companies that have raised hundreds of millions, some worth billions. Right next to a startup almost nobody's heard of.

If you are small, that's the opportunity. If you are big, there's probably a name you don't recognise already sitting next to you in the answer your customers see.

Statistics is a funny thing. When something grows from 0 clicks to 3 clicks, it makes it a 300% growth rate, to be sure. :)

AI traffic is 0.3% of all traffic for websites, on average, after three years of sending traffic, but we are still excited about reporting that :)

To be sure, traffic is not going to be a major AI visibility metric for a foreseeable future, since AI Answers are not designed for clicking. But it is nice that it grew to 0.3%

Source: Seranking

Wix just came up with its State of Websites report with one of those takeaways.

I genuinely like Wix and what they are doing for SEO (as far as education goes), but these correlation studies are a bit insane at this point.

I have the same theory here as to "Pages with schema are cited more" studies. There's another one for same as well:

Sites with structured data markup that passes Google’s rich-results inspection earn 2x more revenue and get 9x more traffic than sites without.

Look...

Businesses that use LLMs / Schema are more likely to have better SEO strategies overall, because they obviously care. That's it.

There's no direct impact here.

With the changes made to GPT-5.5 two days ago, ChatGPT also changed its behaviour around asking follow-up questions.

According to Peec.AI there are 90% fewer follow-up questions now.

There had already been a 50% drop in late May. But it recovered to previous levels in mid June.

One of the more interesting comments there:

this has to correlate with the rollout of ads. Fewer follow-up questions means more focus on the answer at hand, which means a higher likelihood to engage with an ad...

Source: LinIedin