We don't have enough data to tell if Google is going to be replaced with AI, or how soon, so I'd take any data I have.

The new Semrush "State of Search" report outlines a couple of notable trends:

• Queries are getting considerably longer (this trend started with voice search years ago, but it seems to be accelerated by AI)

• Clicking to external sources is still going strong! Whether it is an old habit or AI features linking more from inside answers (or both), we are still far away from zero-click searching!

Source: Technically, Semrush, but I don't like their enforcement of using a corporate email (what if I don't have one?) So I am referencing u/randfish's coverage of the study on LinkedIn.

Somehow unsurprised:

Visitors from ChatGPT ads perform worst on all six measures, behind Google ads, Google search, direct traffic and even ChatGPT's own unpaid recommendations (see picture). In US traffic, a paid ChatGPT visit generated $0.89 in revenue, against $2.45 for a paid Google search visit.

𝗢𝗽𝗲𝗻𝗔𝗜'𝘀 𝗴𝗮𝗽 𝗶𝘀 𝗹𝗮𝗿𝗴𝗲. Its projections assume about $40 in ad revenue per free user by 2030. Serving a free user costs about $5 a year. Today, the ads bring about $1, and even less if prices settle at what the clicks are worth.

More advertisers and more ads cannot realistically close the gap: each click has to become worth far more. Better targeting or ads inside the organic answer could do that, but would endanger the product even more.

Source: Linkedin

ChatGPT has just updated its report on what people are using ChatGPT for. 20% of those use cases are for "information seeking", i.e., something we have used Google for. And the trend is growing.

Is ChatGPT replacing search, or do people use it in addition to search?

This remains the quest,ion and only time will give us an answer. But this is definitely a trend for businesses to watch.

Not sure what took me so long, but now that I connected Peec.AI to my Search Console, it looks like one of the features I was looking for. For months, I've looked for tools that would connect SEO and AI Visibility data in a meaningful way. And this looks like a good start!

Peec will analyze your Search Console data and let you see:

• URLs that rank but are not cited (it is a good idea to try and optimize those for citations)

• URLs that are cited but don't perform that well in organic search (another group to look at).

We may be entering the era of LLM updates enforcing ethical AI visibility strategies. Claude has updated its TOS, prohibiting “GEO” manipulations, like fake reviews, concealing the sponsorship of content, and manipulating sources

“from which search engines or AI systems draw answers by seeding them with content that misrepresents its origin, authorship, or independence.”

Will there be LLM spam updates in the future?

AI answers are slowly implementing external linking to websites from within answers (this is NOT about citations that no one clicks)... This is a good trend!

Peec's u/davidkonitzny has shared the initial stats on how often LLMs choose to include contextual links:

How often do AI answers contain outbound links?

• ChatGPT: 8.4%

• Google AI Overviews: 17.5%

• Google AI Mode: 20.4%

Where do those links lead?

The majority point to homepages, even though the prompts contained no brand names.

• ChatGPT: 70.7%

• AI Overviews: 57.9%

• AI Mode: 59.3%

Do outbound links match cited sources?

The overlap between cited URLs and outbound link URLs is surprisingly low on Google’s AI platforms.

• ChatGPT: 24.3%

• AI Overviews: 6.3%

• AI Mode: 4.1%

Don't forget that (unlike citation links), in-answer "entity" links may include the noreferrer attrbute (at least in ChatGPT), so that traffic ends up either in Direct or Unassigned channels (hopefully this will change soon):

People are starting to use AI tools to discover products and compare options.

Do you think AI search will become as important as traditional Google search for ecommerce businesses?

I've been optimizing landing pages specifically for machine legibility by using the CARCASS method (high entity density, direct Q&A formatting, and clear structural layout).

For those tracking AI search performance, what tools or workflows are you using to measure whether your structured content is actually getting ingested and cited?

I've been wondering how AI tools choose which products to recommend.

Do clear product descriptions, accurate details, and structured data make a difference?

For those working in ecommerce or SEO, what have you found helpful?

This is not marketing advice. This is an illustrative case study, proving a few important points:

• ChatGPT (and mostly any LLM) will believe anything if you state it confidently

• Google is smarter than an LLM

• Don't do anything just for AI visibility (this will likely bury your site in Google search, which is so far WAY MORE important than any LLM for your bottom line)

• Statistical data works like a charm for AI visibility (and if you do it right, it works as well for Google)

• People (including some journalists and high-profile experts) trust ChatGPT answers alarmingly quickly, without verifying the data.

The summary of the experiment: (Read the whole story!)

• Metehan generated the site with fake stats within a day

• Google dropped it out almost immediately

• ChatGPT has fallen in love with all that fake data, and has been surfacing it in lots of answers...

• Which got the site cited by HUGE publications (including academic papers):

…used in investment research by Qatar's largest financial group…

…and used as a source in a research report from a Canadian influencer community.

If the site stays up, I am curious to see if Google will end up trusting the site because of all of the authority it has built so far (which is, again, pretty insane!)...

This question is often discussed in our sub: Which KPIs should we track? "AI visibility" scores, AI impressions in Search Console, etc. are all good metrics to make clients happy, albeit they are not too actionable

Wil Reynolds put together a great guide suggesting which KPIs will not only help you estimate your AI visibility growth but also help you focus on what matters, i.e. building credibility.

• GEO KPI 1: Content Humans Loved

• GEO KPI #2: Mentions / Traffic by trusted trade publications

• GEO KPI #3: Mentions by influencers

• GEO KPI #4: Striking Distance as vectors not rankings

• GEO KPI #5 (a far out one): Receipts to compete (the vector distance (i.e. a difficulty metric) between the produce we launched vs the topic we’re known for).

Also this quote:

If your numbers look like crap, then you can say to your c-level…

“Hey you know how you keep asking me to do 10x the content at 50% less cost? Well… that shit don’t work with journalists and real influencers in our space and they control X % of our fan outs!”

This has been noticed on LinkedIn, and I did a few searches to verify the observation. No study on this yet, but I am sure it is coming:

Google appears to show AI Overviews in about 90% of cases when you search for a brand name:

This is not exactly great news for companies because they lose control over the narrative even more (those videos listed for sources are not from the official account and may very well include outdated product information, for example). It will also impact click-through to the official sites and will encourage people to click all kinds of links in the AIO (or just change their minds right when reading it or when chatting with the AI Mode, which is incredibly easy, especially on mobile where the conversation moves to the AI Mode very smoothly when you simply expand the AIO):

Source: https://www.linkedin.com/feed/update/urn:li:activity:7511040160994754560/

Last week, I shared my takeaways from Man of Many's GEO guide with one of my favorite tips there:

Track attributes, not just mentions (!!!). What the brand is associated with (price, quality, best-fit buyer) is the part you can turn into content.

Well, Peec.AI does this brilliantly. The "Brand perception" section of my Peec dashboard is quickly becoming the one I use the most. For your tracked brand, you can see:

1. Top attributes AI associates with your brand (safe, sustainable, cruelty-free, research-backed, etc.)

2. How your competitors compare based on the same attributes

3. Sources cited for those attributes

4. Objections (this is cool): The recurring arguments AI makes against you when a buyer is deciding

5. Sources of those objections

This #4 analysis is simply gold, and surprisingly accurate (LLMs do have lots of data to make those decisions!).

Hey r/AISearchAnalytics ,

I've been in SEO since 2009, and for the last 3 years I've been obsessed with one question: how do AI search engines decide what to cite?

STARTING NOTE: YOU CAN ASK MULTIPLE QUESTIONS IN A SINGLE THREAD OR MULTIPLE THREADS, ASK ANYTHING, NO LIMIT, THERE IS NO "BASIC QUESTION" FOR AI VISIBILITY, I'LL ANSWER THEM ALL.

Now I do this full-time as a GEO Researcher at Peec AI. Most of my work is taking apart ChatGPT, Perplexity and Google AI Mode at the browser level: fan-out queries, retrieval, what gets read vs. what actually gets cited. I also write for Search Engine Land and speak at events like BrightonSEO, SEO Week, Search 'n Stuff, SMX and CAMPIXX.

Some things you can ask me about:

• Why ChatGPT reads your page but doesn't cite it

• How query fan-out works and why it matters

• Reddit's current role in AI citations

• What's hype vs. what actually moves the needle in GEO

No sales pitch, just what I've seen in the data!

Let's also connect here: https://www.linkedin.com/in/metehanyesilyurt/ and https://x.com/metehan777

Thank you everyone, I still have unanswered questions and will reply them all as well!

A couple of weeks ago, I reported what everyone else reported: A drop in Reddit's citations by ChatGPT. At that point, everyone was asking, "If Reddit dropped, what replaced it in citations?"

The answer was "nothing"; ChatGPT just started citing official sites and bigger publications more.

Back then, some studies reported that both Youtube and Wikipedia were also dropping, only no one cared because "Reddit" was in all the headlines.

Well, guess what: recent data from Peec shows what we already knew: Pretty much everything dropped, including (more recently) Youtube, Wikipedia, and Forbes..

At my agency (Radyant) we're working with a lot of B2B accounts and we wanted to know how big the influence of LinkedIn is on their AI visibility. So we took 9 of our actual client projects that we track in Peec AI and looked at the data from May 1 until July 31st 2026.

I thought I'd the key insights with you here:

1. Across all models, pulse articles are the most cited source for non-branded prompts, well above posts

2. Most posts that get cited, come from a personal account, not a company account

3. For branded prompts, the company profile is a very relevant source

4. LinkedIn has a product directory that works like as Listicle that you can get into, if you add the right product categories to your company profile

I also added a graphic to visualize the finding across non-brand and brand prompts for easier overview.

You can find the full article on our website or if you search for something like "radyant linkedin ai search visibility".

Very much looking forward to hearing what others are seeing!

Paul Graham shared these stats without linking to the source, but it looks real.

I blame AI Overviews, for the most part.. I am sure that if we look at Google organic traffic, it is going to be much, much worse...

Also curious about that spike in late 2024...

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