Subscribe
Share
Share
Embed
All things Generative Engine Optimization (GEO). A breakdown of all that's happening in the world of AI search.
Hi, everybody, and welcome back
to The GEO Show, episode seven.
The GEO Show is brought
to you by GeoForge, full
self-driving for AI visibility.
Now let's get into our stories for today.
The first is that Google says that there's
no special technical GEO layer for Google
AI Search Google's John Mueller said
that there is nothing really special
websites need to do specifically for
generative s- responses in Google Search.
Google's AI results draw from its search
in-index and additional query fan-outs.
So this undercuts a lot of vendors that
are selling mysterious Google GEO hacks.
Um, it does not mean that AI
visibility equals rankings, though.
And of course, it does not apply to
ChatGPT or Claude or Perplexity, but
only to Google's AI results, which is
Google AI Overviews and Google AI Mode.
Um, I'm not sure if I really agree
with this, but I think fundamentally,
uh, Google's position so far has been
that they don't wanna give a lot of
legitimacy to GEO as a discipline,
and they have been saying that
effectively, GEO is just good SEO.
What we're talking about here specifically
is the technical on-page factors.
I do think that this is the area where
SEO and GEO have the most overlap,
where they have the most in common,
which is on page, uh, technical--
the on-page technical foundation.
You want your site to,
to be well-structured.
You want all the content to
be very accessible with a very
logical information architecture
for all, all crawlers to come.
Uh, you do think about things like,
uh, crawl efficiency and indexation,
because if you still wanna be
retrieved in real-time search by
LLMs, of course, you do need to
be indexed by the search engines.
So crawlability and indexation are two
fundamental things that are still there.
Uh, but I do think that broadly
speaking, uh, what Google's John
Mueller is still doing here is trying
to keep, broadly keep everyone focused
on SEO fundamentals and not into
going and chasing, um, some GEO hacks.
So, um, really positioningâ¦
I, I think the advice here would be
positioning technical GEO for Google
really as an extension of strong SEO.
Again, that means crawlability,
information architecture, entity
clarity, useful content, and evidence.
So, uh, differentiation comes
through measurement, proprietary
knowledge, and off-site authority,
but not any sort of secret markup
All right, next story here coming
from the Pew Research Center.
Pew finds that AI f- Pew finds
AI fingerprints on 10% of the
web and 35% of the newer dated
pages since the launch of ChatGPT.
So let's dive into these numbers.
The Pew Research Center analyzed
490,000 English language
websites from Common Crawl.
In its July 2026 sample, 10% of all
of those pages showed meaningful
signs of AI authorship or editing.
And among pages with detectable
publication dates after ChatGPT's
November 2022 launch, that figure was 35%.
So what does that mean?
Uh, more than a third of pages published
since ChatGPT's launch are now showing
up with these so-called AI fingerprints.
Um, that to me is not surprising,
and I bet you if we looked at even
specifically the last, say, six to twelve
months, I'll bet you that that figure
is far, far north of fifty percent.
Uh, this is just the new
reality that we live in now.
Uh, AI content itself is no
longer differentiated in any way.
It's, it's actually the norm,
and it's becoming, uh, ambient
infrastructure, let's call it.
So again, what is the moat for content
creators when you're competing with
everyone else who can produce an
unlimited amount of AI-generated content?
The moat is information gain, which
means things like subject matter
expert interviews, proprietary
datasets that only you own, benchmarks,
original technical analysis, customer
evidence, and first-hand experience.
Information gain for the win.
Okay, next story.
NVIDIA is partnering with Perplexity.
Initially, there was rum- they were
rumored to have, uh, or NVIDIA was
rumored to be eyeing an investment
in Perplexity, which would value
Perplexity at thirty billion dollars.
Uh, but now we have an update to the
story which was published just yesterday.
In fact, no, published today on
Perplexity's own website, and they
have introduced, uh, the partnership
between NVIDIA and Perplexity has
now introduced something called
Portable Computer for local-first AI.
Portable Computer runs Perplexity Computer
entirely on-device with NVIDIA, keeping
private data local and escalating to
the cloud only when a task needs it.
So this is a f-fascinating play.
Uh, I, I think it's-- I don't know
who NVIDIA is not partnering with
in this ecosystem, but this is
the first significant partnership
between NVIDIA and Perplexity.
And as you all may know, NVIDIA has
now produced its own AI computer
or laptop with its own special
chips to be able to run AI locally
on-device, and, uh, sometimes this
is referred to as AI on the edge.
I believe this is where Apple is gonna
be a major, major force in the very
near future So what this is doing here
is that the portable computer is an
NVIDIA-powered computer running a local
model, so nothing ever goes to the cloud
unless it is a task that needs it, and
I don't know how they determine that.
But this is going to be very big for,
uh, companies that really value privacy
and that are not yet willing to send
their proprietary data and their,
their brand's alpha straight up into
cloud-based systems that are hosted
by the likes of OpenAI and Anthropic.
I think it's a, it's a fascinating
play, and I would personally love to
get my hands on portable computer.
I do think it probably needs a
better brand name though from a
marketing perspective, but in any
case, it's a significant move.
All right.
Let's go to the next story.
The first public searchable
ChatGPT Ads library has launched.
So this is coming to us from LLMPulse.
LLMPulse launched an independent ChatGPT
Ads library on August twenty-first and
updated again on August twenty-fourth.
It says that the database currently
contains over seventy-two thousand
observed ads across nine countries.
It's searchable by advertiser, by
message, by country, and by date.
Uh, LLMPulse explicitly states
that this sampled observationalâ¦
this is sampled observational data, but
this is not official OpenAI campaign data.
So bottom line here is that competitive
intelligence around conversational
ads led by ChatGPT Ads is arriving
extremely quickly, and I would not
be surprised if ChatGPT themselves
launches their own official ads
library for research purposes.
We, we have had this for many,
many years, uh, with Google Ads,
um, and the Transparency Center.
We have it as well, of course, with
LinkedIn ads, with Meta ads, and
I do think that the industry does
come to expect this as a sign or
a signal of, of full transparency.
It definitely assists with intelligence
research and competitive research, so I
do think that, uh, LLMPulse was, uh, the
first out of the gate here, but I think
that there will be an official ChatGPT
Ads library, uh, sponsored by OpenAI
in the coming, in the coming future.
And of course, that kind of thing will
spur even more investment in their
ads when you can see the ads that
are running and which ones are, are
being or getting the most success.
All right.
Next story.
Daily AI citations are far noisier
than conventional SEO rankings.
Uh, this is not really breaking news,
but it's further solidifying something
that we, uh, strongly suspect.
Uh, the vendor research here comes
from a company called Chloro, who
compared identical prompts across
consecutive daily runs from August
first through the sixteenth.
A previously cited domain remained cited
the next day only thirty-seven point
eight percent of the time in Google AI
mode, forty-nine point nine percent of
the time in ChatGPT, and sixty-eight point
five percent of the time in Perplexity.
So le-that's actually interesting.
First, that citations are won and lost
effectively on a day-to-day basis.
So it means that you're never
really out of the game, no matter
how small your brand is or how
early you are into the category.
And also, there's a big
difference across, uh, Google AI
mode, ChatGPT, and Perplexity.
Perplexity has the highest, I
would call it citation stickiness
at sixty-eight percent.
Uh, Google AI mode, the lowest stickiness,
or maybe that's the highest slipperiness
at thirty-seven point eight percent.
And ChatGPT right in the
middle at about fifty percent.
So saying that we lost a citation today
is, is basically just statistical noise.
Um, it's not evidence at all that
your optimization has failed.
I think more than ever, when it
comes to reporting on GEO, we need
to take a long-term view, and we
need to look at the trends from
statistically relevant, uh, data.
That means that you can't just run
a prompt once and say that we were
cited and that's a win and that we
expect to be there again tomorrow.
You actually need to run it, in our
experience, probably in the order of
thirty to forty times in a row to get a
statistically relevant, high-confidence,
uh, AI visibility observation out of that.
And then that needs to be repeated.
In our case with SignalForge, we
repeat that every week, and all the
thirty prompts that we track will
run on a cadence of forty runs every
seven days, and that gives us a very,
very tight margin of error, uh, at
around plus or minus two percent.
So the takeaway here is never
report GEO from single executions.
Always use repeated runs, rolling
averages, and confidence bands,
especially for executive dashboards.
Otherwise, you're really just
misrepresenting the data.
On to the next story.
Muck Rack's two-- twenty-five million
link data set reinforces that AI source
strategy must be platform-specific.
Muck Rack's August twenty-fourth
analysis draws on more than
twenty-five million cited links
across ChatGPT, Gemini, and Claude.
It says citation behavior varies
materially by platform and by query
type, and more than half of journalism
citations came from content published
within the previous twelve months.
Its underlying research found industry
trend queries cite journalism at more
than twice the rate of how-to queries.
So that is a big win
for classic journalism.
Um, this adage of get more
PR is, is really too crude.
I think we have to look more deeply
at relevant publication plus topic
plus model combination, uh, which
is a lot more nuanced, in fact.
So this is a very interesting study, um,
and as we've seen and discussed many times
throughout several episodes on this show
here, there is so much variability by
platform, there's enormous variability by
query type, and then of course, you have
jour-journalists publications versus, um,
non-journalistic publications, I'd say.
And that also is very, uh,
carries a lot of weight.
So one of, one of my takeaways here is
that if you can get cited in reputable
journalism sources, then typically this
is gonna have a much greater weighting,
especially if it's something that's
published within the last twelve months.
If it's fresh, uh, that's gonna give
you an outsized advantage, um, but
it is something that needs to be
analyzed on a case-by-case basis.
Publication plus topic
plus model combination.
All right.
And one last adage there
is about domain authority.
Uh, we really don't look at domain
authority or domain rating anymore
at all as a signal, uh, because AI
doesn't care about the link profile.
AI, as far as we know, when it
chooses citations, does not look
at a, a domain-level type of
authority score or a domain rating.
Uh, that's really something from the SEO
days that has not carried over to GEO.
It's all about relevancy.
So if you have a niche publication that
is super relevant, it's better to get
cited in that source rather than to go
for something purely on a high domain
rating or domain authority score alone.
All right.
Now let's wrap up with the
last story of the day, and
that's about agent experience.
Agent experience is emerging as
the discipline that's immediately
downstream of GEO RedMonk's August
twenty-fourth framework distinguishes
GEO from agent experience.
So it distinguishes Generative Engine
Optimization from Agent Experience or AX.
GEO gets a product discovered or
recommended, whereas AX determines
whether an agent can actually use it.
It frames, it frames GEO as upstream
discovery and AX around access,
context, tools, and orchestration.
So we're moving from a world
of can AI recommend us to a
world of can AI operate us?
And we're starting to see this and talk
about this with some e-commerce clients.
But I do think this is a longer-term
view here that agents now are
coming and crawling en masse.
They're crawling websites at a much
higher rate now than, than human visitors,
uh, and that, that is, has been proven.
But what comes next after the crawl?
And that's gonna be that agents are
gonna start to use these websites, and
we're seeing this now with tools like,
um, Grokbot, which I've been testing,
where every single Grokbot agent has
its own computer in the cloud, and it's
using, it's using websites like humans.
Um, Claude is doing this much, much
faster with every passing month.
The, uh, the Chrome extension that
allows Claude to operate Chrome as
a user, it's working really well.
Uh, ChatGPT's browser, uh, browser
control is working very fast.
So more and more, we are moving into this
era of agent experience, and we need to be
thinking about websites not only through
the lens of user experience, human user
experience, but also agent experience.
So the agent comes and crawls, and,
and you have to make sure that it can
crawl effe-efficiently and effectively.
But also, if an agent is going to
fill out forms, if an agent is going
to transact or take specific actions
on a website, let's say do a search,
create filters, um, generate some kind
of result, that experience for that
agent also needs to be very smooth.
And this is very logical that it
flows downstream from GEO because
it flows downstream from an
agent's crawl visit to discover
the information as the first step.
So that's gonna be something we're gonna
be watching a whole lot of in the future.
And that brings us to
the end of this episode.
Thank you all for tuning in, and
we'll see you on the next one.