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All things Generative Engine Optimization (GEO). A breakdown of all that's happening in the world of AI search.
Hi, everybody.
Welcome back to another
episode of The GEO Show.
I'm your host, Paris
Childress from GEOForge, the
self-driving-- full self-driving
platform for AI visibility.
Check it out at getgeoforge.com.
So let's get right into our top stories
of the day, and, uh, we've got a nice full
docket here ahead of us with ten stories.
So let's start with number one.
Uh, two fresh datasets show the
same pattern, which is less organic
traffic but higher intent AI visitors.
So an agency called First Page Sage
analyzed three point four billion
sessions, that's billion sessions,
across two hundred and eighteen client
sites, and they report that, uhâ¦
I'm sorry, across two hundred and
eighteen client sites and reports B2B
SaaS organic sessions are down twenty-nine
percent to twenty-nine point four percent
from its normalized baseline, while
AI platforms now account for eleven
point eight percent of SaaS sessions.
So this is particularly, uh,
research for the SaaS business.
ChatGPT referrals converted to leads
at four point seven percent versus
just one point nine percent for
Google Organic, so roughly a three
x increase in the conversion rate.
Separately, Brainlabs data covering
fifty-four advertisers found that
organic sessions are down ten point
five percent and r- AI referrals are
up a hundred and sixty-three percent,
and AI-driven key events are up three
hundred and thirty-five percent.
So the interpretation here really is
that AI traffic is not replacing every
lost SEO click, uh, but the visitors
that do arrive from AI-referred
traffic are arriving much further down
the buyer's journey, and therefore
they have a much higher conversion
rate, as we've seen with this data.
And that's particularly
true with SaaS businesses.
And really that makes a lot of
sense to me, having worked with, uh,
dozens and dozens of SaaS businesses.
Uh, it's very clear now that a lot
of that research has collapsed.
The, the buyers-- the buyer journey has
effectively collapsed, going from multiple
searches a few years ago now to long
single-threaded conversations with LLMs.
And by the time someone does arrive at
your website, they are much, much more
educated from that conversation and
much more likely to be ready to convert.
In fact, the intent on coming to
your website is actually to convert.
They're coming with navigational intent.
So really, uh, if-- I, I would advise
against evaluating GEO primarily by
its referral traffic that it brings to
your website, um, especially with SaaS.
I think what you wanna do is think about
this as a journey or a funnel that starts
with AI exposure of your brand, which
then generates branded demand, which then
will lead to qualified visits and then
on to, let's say, a demo or an MQL lead
capture, followed by real sales pipeline.
I think that is the best way for a SaaS
company to evaluate the full impact,
the full funnel impact of, uh, their
investments in AI and GEO Number two story
of the day is a company called Keenable.
Uh, Keenable has raised
$26 million to build a
search engine specifically for AI agents.
Keenable emerged from stealth
on August 25th and secured a $26
million seed round led by Excel.
They are founded by former Yandex search
AI, uh, by former Yandex search AI
executive Andrey Styshin and Mateus Patri.
And it says that it has indexed more
than 100 billion documents and is already
serving AI labs and inference providers.
Uh, so, uh, it may seem crazy to, to be
launching a new search engine now, but,
uh, this, this company is launching a
search engine specifically for AI agents,
which I find to be very interesting
because right now, uh, most of the, uh,
let's say the real-time, the real-time
search that is happening, uh, with LLMs
is primarily going out to Google and to
Bing, the, the dominant search engines.
But I do think that AI, especially,
uh, if AI is provided with, uh, search
engines that are tailored specifically
for, for AI agents, I do think that they
would also, uh, reach out and try to get
those results from other sources as well.
So the retrieval layer beneath AI
assistance is actually becoming a
standalone infrastructure market.
Uh, and I don't think it's fair to assume
that Google and Bing are going to remain
the only gateways to the web for agents
All right, moving on to the next story.
Uh, Featured launched-- A company called
Featured launched a GEO-to-digital
PR workflow with data that challenges
traditional authority targeting.
Let's unpack this.
Uh, Featured's August report has
analyzed twenty-two thousand eight
hundred and eighty-one Perplexity
citations across eleven thousand
four hundred and ninety-nine domains.
It found that thirty-four point five
percent of citations came from domains
with Moz domain authority below forty.
In a classified subset, editorial
sources represented sixty-four percent
of citations, while brand-owned content
represented only one point seven percent.
Featured simultaneously, Featured
simultaneously launched a GEO audit
intended to identify the publisher's AI
engine site and turn them into PR targets.
The citationsâ¦
The citation figures are
Perplexity-specific and can't be
generalized across all other engines.
So, uh, this is interesting.
There's a lot of statistics here.
Um, thirty-four percent of citations
coming from low domain authority sites
with domain authority below forty.
So this is not a game of chasing
after high domain authority,
uh, websites for your citations.
Uh, that's something that we
covered in the last episode.
And also, interestingly, editorial sources
at sixty-four percent with brand-owned
content only at one point seven percent.
So that's kind of a signal for how
much effort you should be putting
into off-site GEO and citation
building versus, uh, on-site or,
uh, on-site content publishing.
So really, the off-site GEO game
is increasingly looking like a
citation-informed digital PR,
not really conventional high
domain authority link building.
So the advice here really would be
to build your outreach lists and your
outreach targets from the publications
that are actually appearing in
buyer prompt citations, not from
generic, uh, DR or DA thresholds.
And in fact, this is the approach that
we take with Site Forge, which is the
citation building module inside of GEO
Forge, which is that we are pulling all
of the citation opportunities directly
from the citation sources of the prompts
that we're tracking so that the users
can really go after those specific
publications rather than just trying
to chase after high, uh, domain rating,
high DA websites in their category.
So that's great to see that this
research is supporting our approach.
Next story is about Webflow.
Webflow can now let Codex and ChatGPT
audit and modify websites directly.
Uh, Webflow's August twenty-fourth
integration brings its MCP-powered
capabilities into Codex and ChatGPT.
The built-in workflows include
SEO and answer engine optimization
audits, accessibility checks, broken
link detection, CMS management, safe
publishing, and development work.
Webflow, uh, has been, at in my opinion,
really at the forefront of AEO and
GEO for at least the last year, and
this new MCP-powered integration with
Codex and ChatGPT is a really big deal.
Uh, I have been using the Webflow
connector in Claude for many months,
and I have found it to be increasingly
more powerful, uh, not only for
publishing directly into my CMS, but
to run, uh, audits and checks onâ¦
I, I can, for example, check my schema.org
snippets across my entire blog
and get that diagnosed and
improved through the Claude MCP.
So it's more good news that this is now
has been extended to ChatGPT's ecosystem
through, uh, its Codex, uh, the Codex MCP.
So I think really what this means for
the, the practitioners out there is that
the, uh, audit work is p- increasingly
becoming automated through MCP connectors.
So to say that we audit your website
and we can fix the metadata, we can
fix the content, that's really losing
value as an agency proposition.
I think that the premium layer
now becomes strategy, proprietary
knowledge, experimentation, QA,
and, uh, and just knowing which
changes really matter commercially.
But the pure audit work hasâ¦
is really now going to AI.
Okay.
Next story.
Free GEO measurement is moving into
the actual consumer AI interface.
So a company called BrowserAct launched a
free GEO report on August twenty-fifth for
ChatGPT, Claude, Gemini, and Perplexity.
And unlike most AP-- uh, API-based
trackers, it executes questions
inside a consumer web interface,
and it preserves the prompt, the
visible answer, the citations.
It takes screenshots.
It preserves language and market
BrowserAct explicitly describes
each report as a snapshot
rather than ongoing monitoring.
So I think this is a very interesting
new meth-- uh, measurement methodology
because most of the tools, as far
as I know now, uh, practically a
hundred percent of the AI visibility
tracking tools are API-based.
And I'm pretty sure that the results
and answers that you get through
that API are different than what
a real user would get, uh, when
they actually go through a browser.
So I think it's very interesting
to see that this company is now
taking the, uh, the browser approach
with browser, uh, BrowserAct.
So, um, the measurement methodology
really is becoming a differentiator
here, and I'd be interested to
see, uh, how their results differ
from the API-driven trackers.
All right.
Let's go to the next story.
Buyers are funding GEO, but
mostly still call it SEO.
A company called Fractal has surveyed
three hundred and forty-three
US marketing decision-makers.
Eighty-one percent still describe AI
search visibility internally as SEO.
While marketers report allocating an
average twenty-four percent of search
and content budgets to AI visibility.
Two-thirds have already used ChatGPT,
Gemini, Perplexity, or similar
tools to evaluate marketing vendors.
So the takeaway here is that the
budget is moving across the aisle
faster than the terminology being, uh,
meaning, uh, the, the aisle meaning
the crossover from SEO into GEO.
So really for practitioners, agencies,
I would say lead with pitches that
solve the business problem, which
is SEO plus visibility in AI search.
In my experience, I think it is
still good to ef-- essentially to
bundle those two concepts together.
Um, you can explain GEO after that and,
and how it is differentiated, but I
think still the market wants solutions
that will solve for both SEO, which
is still very relevant, and for GEO.
All right, next story.
New monitoring data shows AI
engines are consuming radically
different amounts of evidence.
PromptScout's updated dataset
covers five thousand four hundred
and thirty-six completed answers
across five engines
Its panel found median source counts
per answer of thirty-eight for
ChatGPT, fifteen for Perplexity,
seven for AI Overviews, and six for
Gemini, and three for Bing Copilot.
The track prompts skewed towards
B2B software and local services,
so the exact figures should
be treated as panel-specific.
So that is quite interesting that we're
talking about the number of citations
that are listed as sources in an answer.
So clearly, ChatGPT, uh, has provided
the most with thirty-eight on average.
Perplexity number two at fifteen,
AI Overview is just seven, and
similarly six for Gemini, and
then only three for Bing Copilot.
Um, so that's, uh, that's
kind of interesting.
A specialist page may have a realistic
shot at getting into ChatGPT for
a citation, but, you know, a, a
more of a long shot, let's say, for
getting into Google AI Overviews,
which has, uh, on average just a
fraction of the number of citations.
So I think it's really important
strategically to measure really
which sources each priority
engine uses for a client category.
And, uh, I would say if you wanna
get-- if you really wanna win AI
citations in Google AI Overviews with
limited, with the limited shelf space
that's there, I would really lean
heavily into YouTube videos primarily.
Whereas with ChatGPT, uh, it's a
much more varied source, uh, group
of sources, so I think there you can
do more of a classic PR outreach to,
um, to other third-party websites
So clearly is there is not one
universal, uh, citation building
strategy or GEO content strategy.
You really have to look at model by model.
Okay, moving on to the
next sto-story here.
A GEO case study exposes the gap
between cited and being known.
Seek Labs reports one site reaching
four hundred and fifty-one citations
across three hundred and ten pages,
with citations rising eighty-two
point six percent, while brand
mentions rose only ten percent.
The resulting citation to mention ratio
was roughly eight point five to one.
And now this is just one client case.
It's not a controlled experiment,
um, but what this is showing
potentially is that an AI system
can repeatedly use a company's
content while barely strengthening
the company's brand presence.
And, uh, we see this in our data as well.
Uh, it's, it's typically easier to get
a citation than to get a brand mention,
but getting a brand mention, meaning
that AI is naming your brand in its
answer, is way, way more valuable.
So I think what we really advise
here is to measure at least
three outcomes separately.
You wanna measure the citation from a s-
a source citation, which typically means
you're, you're coming up as one of the
listed citation sources in the right-hand
panel sitting next to an AI's answer.
You also wanna track your brand mentions
in the answer, meaning just how many
times your brand is appearing at all.
And last, you wanna see if you are
recommended with positive sentiment.
So that's also important as well.
Sometimes it, it could be, uh,
something negative said about your
brand, which, which might be damaging.
So, uh, content optimization can win
the first one, which means you can win
a citation, but it doesn't necessarily
mean that you win the other two,
meaning that you might not win the,
the brand mention or the recommendation
inside of the answer itself All right.
Moving on to the next story.
Some GEO losses cannot be
fixed by marketing alone.
Search Engine Land reports examples
where sophisticated brands were
omitted from AI recommendations because
available evidence surfaced real
issues such as missing integrations,
support problems, reliability concerns,
or product limitations, not because
AI failed to discover the brand.
So the takeaway here is that GEO
is also becoming a customer and a
product intelligence system beyond
just a recommendation engine.
Sometimes the model's recommendation
is telling you something that's
uncomfortable, but it is useful.
So a strong GEO engagement should
diagnose why a client's, uh, why a
particular client loses recommendations
and route those find- findings to
product or customer success or support
or leadership, um, when content alone
can't solve the underlying problem.
So I think it's very interesting that, uh,
you could be a very well-known brand, um,
but if you do have, uh, issues that are
surfacing, AI could tell that ugly truth.
And, uh, and it's, it's important not
to just contain that within marketing
and to try to, you know, solve that
with educating AI, but also to flow
that very useful information to other
departments and, and other parts of
the business that can, that can learn
from that and fix it at the source.
All right, on to the last story of
this episode, which is brand accuracy
needs to become a GEO KPI, and this is
building on the last, on the last update.
An imp-Imperva rank audit tested
one thousand two hundred and
fifty-seven factual claims across
one hundred and eighty-two businesses
recommended by a search-enabled OpenAI
configuration.
Twenty-four claims, or one point nine
percent, contradicted available evidence,
but twenty businesses, or eleven percent,
had at least one incorrect claim.
Another thirty-eight percent of claims
were unsupported rather than proven false.
So the study used one frozen
OpenAI configuration and automated
quality con- and automated quality
control, so it is a snapshot
rather than a universal error rate.
So this is shining a
spotlight on accuracy.
Most of the GEO space right now is focused
on discoverability, uh, getting your
brand to simply show up in an AI response.
But factur-factual accuracy, I
think, is the other side of the coin.
If you're showing up but AI is giving
the wrong information about your
brand, or it could be that users are
even using your brand in their prompt,
they're asking questions about you, uh,
it's ex-extremely important that AI is
gonna give factually, factually correct
and accurate infor-information back.
If it doesn't, let's say if it
hallucinates something or if it just
simply gets a, a data point wrong,
then it can do damage to the brand.
So I think not only auditing how often
you appear and whether you appear as
a mention versus as a citation, it's
also important to really understand
what AI says about things like your
certifications, your compliance, your
integrations, uh, your deployment models,
your pricing capabilities, uh, security
claims, and, uh, basically whether public
evidence supports those statements.
And if that is incorrect, then I would
suggest going to the sources in your
website and around the web and trying
to correct that information so that
you can, uh, really shape the degree of
accuracy that AI says about your brand.
So keep that in mind.
It's not only a game of visibility, but
it is also a game of brand accuracy.
All right.
With that, we've come to
the end of this episode.
Thanks again for tuning in, and
we'll see you on the next one.
Bye everybody.