Imagine spending years, you know, building out
your website, carefully crafting all that content.
And then you find out that nearly 70 % of Google
searches, they now end with zero clicks to any
website. Zero. It's pretty shocking, right? That's
the reality with these AI search systems. It
honestly feels like the ground under traditional
SEO just vanished. For anyone creating content,
this isn't just interesting. It's basically an
urgent survival manual we're talking about today.
Welcome back to the Deep Dive. We looked at everything
you sent us this week, articles, research, guides,
and the theme was overwhelming. This huge shift,
these AI systems, they're answering questions
directly now, which means the old rules for getting
seen online, they're, well, they're gone. So
our mission today is simple. Cut through all
that noise and give you the new rulebook. We're
going to define the new goals, what it means
to get cited versus just mentioned, which is
crucial. We'll explain how AI actually picks
its sources, this ARAG thing, and the practical
part, the step -by -step odd -go framework, how
to structure your stuff to win. Okay, let's start
with this idea of an apocalypse. Is it really
that bad? For, what, the last 20 years, everything
online was built around the click. traditional
seo it was all about optimizing keywords chasing
backlinks tweaking those meta descriptions everything
was aimed at getting someone a user to land on
your page right get the click but now systems
like perplexity google's ai overviews they kind
of step in front of that they give the answer
synthesized and complete Right there on the results
page. And that's how you get that 70 % zero -click
number. It sounds terrifying, I know. But maybe
this apocalypse is actually forcing a really
important correction. It's pushing us away from
just sheer quantity towards actual quality. Verified
quality. Yeah, the AI is sort of clearing out
the low intent noise for us. Exactly. And here's
where it gets really interesting. Like you said,
the counterintuitive part in all the sources
we read, the visitors who do still click through
after seeing an AI summary, they're highly pre
-qualified. They aren't just kicking tires. They
already know the basics. The AI gave them that.
So they have specific high intent needs. the
ai filtered them for you that's the absolute
key difference and the early research it suggests
traffic from these ai recommendations could be
worth get this 4 .4 times more than your standard
organic visitors 4 .4 times that's a huge multiplier
it's a fundamental value exchange yeah okay but
are we sure i mean is this just uh wishful thinking
from people seeing their traffic drop by half
beat how solid is that 4 .4 x number well the
data we have points to that intense shift. Think
of it like this. Maybe traditional SEO brought
100 people to your open house just browsing AI
search. It brings maybe 20 people, but they're
pre -approved buyers. They're ready. That targeted
traffic just converts way better, way faster.
OK, so if overall traffic volume dips, but the
value of each visitor potentially quadruples.
How should we be measuring success now? What's
the real measure? Success pivots completely.
You stop chasing raw volume and start tracking
the quality, the intent of those super filtered
visitors. All right. To navigate this, we really
need to get the language right. The new acronyms,
traditional SEO, search engine optimization.
It's still essential. It's the foundation. The
AI has to be able to find you in the first place.
Cable stakes. But just doing SEO now, it's not
enough. It's like, ah, you got invited to the
party, but nobody's asking you to dance. Right.
So there are three key acronyms now defining
this new visibility game. First, SEO. Still focused
on clicks, getting high rankings in those classic
blue links. That's its job. Okay, the foundation.
And then we move into the AI -specific goals.
Exactly. Next up is GEO, generative engine optimization.
The goal here is citations. This means you want
the AI to actually reference your site with a
link as a trusted source, like the AI explicitly
says, according to your website .com. You become
the quoted expert in the AI's answer. Precisely.
And then the top tier, the ultimate goal, that's
AEO, AI generation optimization. Okay. Here.
The goal is mentions. This is where your brand,
your product gets recommended directly as the
solution, often without even needing a direct
link right in that sentence. Ah, so it's integrated
more deeply. Way more powerful. The AI might
say something like, for ease of use, the kit
platform is often cited as an excellent choice.
your brand becomes part of the AI's core sort
of unbiased recommended knowledge. That distinction
feels really critical because most businesses
are probably still stuck fighting the old SEO
battle. While they're losing this much more valuable
GEO and Ego World War, exactly. So let's nail
this down. What is the core difference between
just getting cited GEO versus being mentioned
as the solution Ego? Okay, GEO means the AI quotes
you. Ego means your brand becomes part of the
AI's actual... recommendation. It's core knowledge.
Right. So how does the AI actually choose who
to quote or mention? The old way was PageRank,
right? Backlinks, domain authority. Yeah, that
was the old engine. The new way AI systems pick
sources, totally different. They primarily use
something called RAG. RAG. R -RAG stands for
Retrieval Augmented Generation. Basically, it's
a multi -step process. It finds relevant info
based on meaning, not just keywords. It uses
things like vector embeddings. Then it retrieves
the best snippets of text, synthesizes them into
a coherent answer, and ideally attributes the
source. So RA means the content itself needs
to make sense, like structurally and semantically,
not just have the right keywords stuffed in.
Exactly. It's judging how good an ingredient
your content is for the final answer it's cooking
up. And to make it trickier, AI isn't just one
thing. Different systems kind of have different
personalities when they pick sources. So you
need tailored strategies. Ah, okay. Not a one
-size -fits -all approach then. Definitely not.
We need to think about at least three key personalities.
First, chat GPT. Think of it as the authority
seeker. It really favors big, established publications.
New York Times, Harvard Business Review, academic
papers. So your strategy there. Deep, well -researched
thought leadership. Clear author expertise is
vital. Okay. Authority seeker. Got it. Who's
next? Then you've got Google AI overviews. Right.
I'd call this one the broad aggregator. It pulls
from a much wider net. Community stuff like Reddit,
Quora, even video snippets from YouTube. So for
Google's AI, you need to be in more places. Yeah,
content on multiple platforms directly answer
questions people ask in those communities. Video
helps too. And the third one? Perplexity. Think
of this as the expert curator. Perplexity loves
specialized review sites, detailed technical
documentation, deep dive analyses. If you want
to satisfy perplexity, you need specifics, data,
benchmarks, really detailed comparisons. Whoa.
Okay. That's that's a lot. It sounds less like
writing an article and more like building, I
don't know, content architecture layered three
ways deep. Yeah. I mean, imagine trying to scale
that structure to satisfy like a billion different
queries across three systems that want fundamentally
different things. It's intense. It really means
you can't just write one blog post and, you know,
hope it works everywhere anymore. So does Argyr
more about how well the content is structured
for it to pull out info or is it just about the
overall authority like the source? Oh, structure
is absolutely key. RAG actively looks for formats
it can read easily. Clear, defined content makes
for a much better ingredient in its synthesis
process. Okay, so if RAG needs this highly structured
AI readable stuff, we need a plan, a concrete
plan. How do we actually do that? How do we restructure
content? Right. This brings us to the AG framework.
It's basically four steps to make your content
AI ready, but critically still engaging for actual
humans. Okay. Four steps. Let's hear them. Step
one, hook the humans, but scaffold it for the
AI. This means every important piece of content.
It must start with the TLDR box. Too long, didn't
read. Right. The TLDR gives the human reader
instant value, which is great. But for the AI?
For the AI, it provides structured, citable facts
right at the top. Super easy for it to pull out.
And crucially, right there near the top, you
have to display your authority signals, author
credentials, expertise. Don't bury them. Okay.
TLDR and authority up front. Step two. Step two.
Build atomic answer blocks. Stop writing long,
rambling essays. Think of your content as a collection
of standalone, answerable units. The structure
here is pretty much non -negotiable, and each
two -header framed as a specific question. right
below it, a direct answer. Then follow that with
a key data point or evidence and cite your source
if possible. Atomic blocks. So the AI can just
cherry pick the one specific bit it needs for
a particular query. Makes sense. If the answer
is buried deep in a long paragraph, the AI might
just skip it. Exactly. You know, I still kind
of wrestle with prompt drift myself sometimes,
especially trying to nail that TLDR box just
perfectly for extraction. It's genuinely hard
work to distill deep insights into... like three
bullet points that actually capture everything.
Yeah, I can imagine. Okay, step three. Step three,
add evidence and structure. AI loves clear structure
because it's predictable, reliable. So use comparison
charts, data tables, step -by -step processes,
really lean into those. The sources we looked
at also emphasized using the before -after scenario
structure. Ah, like showing the impact. Yeah,
illustrating that shift you mentioned earlier,
like we had 12 ,500 visitors converting at 2
.1%. Now we have 9 ,800 converting at 4 .7%.
Specific comparable data is highly citable. Got
it. Concrete evidence and the last step. Step
four, layer in those authority signals. We mentioned
putting them up front, but you need them woven
throughout too. This is EEAT. Experience, expertise,
authoritativeness, and trustworthiness. Think
of EEAT as the AI gatekeeper's main checklist.
Use specific language that signals experience
like, in our internal testing across 500 campaigns,
or based on my direct experience running X for
five years. reference external reports for authoritativeness.
Right. Prove it. Don't just claim it. Okay. So
on EET, what's the element authors most often
neglect when they try to apply this framework?
It's usually experience. They tell you what they
know, but they totally fail to show how they
learned it. You need that proof of work, those
specific examples. Okay. Knowing the theory is
one thing, but putting it into practice needs
a clear plan. The sources laid out a kind of
30 day ago optimization plan, right? Focused
on thousands. Yeah. Pretty straightforward. Week
one is audit. Find your top, say, 10 high -value
topics. Then critically analyze how ChatGPT,
Google AI, and Perplexity are answering questions
about those topics right now. See what sources
they're using. Okay, audit first, then. Week
two is create. Take that high -value content
you identified and rewrite it using the full
Ikigo framework we just discussed. TLDR box,
atomic blocks, structured evidence, EET signals.
And the final phase? Week four is measure. This
is where you intentionally shift your metrics.
Get away from vanity metrics like raw traffic
volume. Focus on what actually matters now. Which
brings us to the new metrics. These are how we
track if this ego stuff is actually working.
Exactly. You need to track AI citation frequency.
How often is your content explicitly linked or
cited by the AI? That's GEO success. Okay. Then
AI referral traffic quality. Yeah. What are the
actual conversion rates of the visitors the AI
does send you? Are they really 4 .4 times more
valuable? And a third. And the brand mention
rate. Even without a direct link in that specific
answer, how often is your brand just named as
a solution? That's ego success. That authority
is the new gold. Right, becoming part of the
AI's knowledge base. Okay, let's quickly touch
on mistakes to avoid. What trips people up? Number
one biggest mistake. Optimizing only for one
AI system. You build great stuff for ChatGPT's
preferences, but ignore Google AI or perplexity.
You're limiting your reach massively because
of those different personalities. Okay, don't
put all your eggs in one AI basket. Mistake two.
Neglecting the human reader. Don't make your
content so rigidly structured that it sounds
like a robot wrote it. It has to serve both AI
extraction and genuine human engagement. It's
a balance. Good point. And number three. Hiding
your credentials. Burying the author bio, not
stating expertise clearly up front. Remember,
AI needs those EET trust signals immediately.
Don't make it hunt for them on some buried about
us page. Makes sense. So besides just not hiding
credentials, what's one quick, immediate fix
most businesses could probably make in that first
audit week to boost their EET signals? Be specific
with dates and sources. Instead of saying studies
show, say, a 2024 Gartner report found, include
dates on your own data, like in our Q3 testing.
Specificity builds trust and authoritativeness
quickly. Hashtag tag tags ultra -crime. Okay,
let's bring it all home. The big idea that really
ties all this together, traditional SEO, that
was a fight for clicks. This new game, GEO and
a Go, it's fundamentally different. It's about
becoming the trusted go -to source that AI systems
actively cite and recommend. and the advantage
this framework gives you a huge head start while
your competitors are maybe still chasing those
vanishing raw traffic numbers you're positioning
yourself to capture the highest value users the
ones who actually convert you know the question
really isn't if ai search will dominate everything
it pretty much already is the real question is
will you be the source it recommends when it
does so here's your challenge your takeaway from
this deep dive choose one core topic that's really
important to you or your business create your
first ago optimized asset for it build that tldr
box structure those answer blocks layer in the
EAT and then actively test it go ask chat GPT
perplexity Google AI overview questions related
to your topic see if your content starts showing
up see if you get cited that's the path forward
out to your own music begins