WEBVTT

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Imagine spending years, you know, building out

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your website, carefully crafting all that content.

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And then you find out that nearly 70 % of Google

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searches, they now end with zero clicks to any

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website. Zero. It's pretty shocking, right? That's

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the reality with these AI search systems. It

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honestly feels like the ground under traditional

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SEO just vanished. For anyone creating content,

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this isn't just interesting. It's basically an

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urgent survival manual we're talking about today.

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Welcome back to the Deep Dive. We looked at everything

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you sent us this week, articles, research, guides,

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and the theme was overwhelming. This huge shift,

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these AI systems, they're answering questions

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directly now, which means the old rules for getting

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seen online, they're, well, they're gone. So

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our mission today is simple. Cut through all

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that noise and give you the new rulebook. We're

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going to define the new goals, what it means

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to get cited versus just mentioned, which is

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crucial. We'll explain how AI actually picks

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its sources, this ARAG thing, and the practical

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part, the step -by -step odd -go framework, how

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to structure your stuff to win. Okay, let's start

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with this idea of an apocalypse. Is it really

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that bad? For, what, the last 20 years, everything

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online was built around the click. traditional

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seo it was all about optimizing keywords chasing

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backlinks tweaking those meta descriptions everything

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was aimed at getting someone a user to land on

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your page right get the click but now systems

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like perplexity google's ai overviews they kind

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of step in front of that they give the answer

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synthesized and complete Right there on the results

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page. And that's how you get that 70 % zero -click

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number. It sounds terrifying, I know. But maybe

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this apocalypse is actually forcing a really

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important correction. It's pushing us away from

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just sheer quantity towards actual quality. Verified

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quality. Yeah, the AI is sort of clearing out

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the low intent noise for us. Exactly. And here's

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where it gets really interesting. Like you said,

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the counterintuitive part in all the sources

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we read, the visitors who do still click through

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after seeing an AI summary, they're highly pre

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-qualified. They aren't just kicking tires. They

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already know the basics. The AI gave them that.

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So they have specific high intent needs. the

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ai filtered them for you that's the absolute

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key difference and the early research it suggests

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traffic from these ai recommendations could be

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worth get this 4 .4 times more than your standard

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organic visitors 4 .4 times that's a huge multiplier

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it's a fundamental value exchange yeah okay but

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are we sure i mean is this just uh wishful thinking

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from people seeing their traffic drop by half

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beat how solid is that 4 .4 x number well the

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data we have points to that intense shift. Think

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of it like this. Maybe traditional SEO brought

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100 people to your open house just browsing AI

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search. It brings maybe 20 people, but they're

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pre -approved buyers. They're ready. That targeted

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traffic just converts way better, way faster.

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OK, so if overall traffic volume dips, but the

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value of each visitor potentially quadruples.

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How should we be measuring success now? What's

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the real measure? Success pivots completely.

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You stop chasing raw volume and start tracking

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the quality, the intent of those super filtered

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visitors. All right. To navigate this, we really

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need to get the language right. The new acronyms,

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traditional SEO, search engine optimization.

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It's still essential. It's the foundation. The

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AI has to be able to find you in the first place.

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Cable stakes. But just doing SEO now, it's not

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enough. It's like, ah, you got invited to the

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party, but nobody's asking you to dance. Right.

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So there are three key acronyms now defining

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this new visibility game. First, SEO. Still focused

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on clicks, getting high rankings in those classic

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blue links. That's its job. Okay, the foundation.

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And then we move into the AI -specific goals.

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Exactly. Next up is GEO, generative engine optimization.

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The goal here is citations. This means you want

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the AI to actually reference your site with a

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link as a trusted source, like the AI explicitly

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says, according to your website .com. You become

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the quoted expert in the AI's answer. Precisely.

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And then the top tier, the ultimate goal, that's

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AEO, AI generation optimization. Okay. Here.

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The goal is mentions. This is where your brand,

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your product gets recommended directly as the

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solution, often without even needing a direct

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link right in that sentence. Ah, so it's integrated

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more deeply. Way more powerful. The AI might

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say something like, for ease of use, the kit

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platform is often cited as an excellent choice.

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your brand becomes part of the AI's core sort

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of unbiased recommended knowledge. That distinction

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feels really critical because most businesses

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are probably still stuck fighting the old SEO

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battle. While they're losing this much more valuable

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GEO and Ego World War, exactly. So let's nail

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this down. What is the core difference between

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just getting cited GEO versus being mentioned

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as the solution Ego? Okay, GEO means the AI quotes

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you. Ego means your brand becomes part of the

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AI's actual... recommendation. It's core knowledge.

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Right. So how does the AI actually choose who

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to quote or mention? The old way was PageRank,

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right? Backlinks, domain authority. Yeah, that

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was the old engine. The new way AI systems pick

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sources, totally different. They primarily use

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something called RAG. RAG. R -RAG stands for

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Retrieval Augmented Generation. Basically, it's

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a multi -step process. It finds relevant info

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based on meaning, not just keywords. It uses

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things like vector embeddings. Then it retrieves

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the best snippets of text, synthesizes them into

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a coherent answer, and ideally attributes the

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source. So RA means the content itself needs

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to make sense, like structurally and semantically,

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not just have the right keywords stuffed in.

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Exactly. It's judging how good an ingredient

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your content is for the final answer it's cooking

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up. And to make it trickier, AI isn't just one

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thing. Different systems kind of have different

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personalities when they pick sources. So you

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need tailored strategies. Ah, okay. Not a one

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-size -fits -all approach then. Definitely not.

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We need to think about at least three key personalities.

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First, chat GPT. Think of it as the authority

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seeker. It really favors big, established publications.

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New York Times, Harvard Business Review, academic

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papers. So your strategy there. Deep, well -researched

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thought leadership. Clear author expertise is

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vital. Okay. Authority seeker. Got it. Who's

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next? Then you've got Google AI overviews. Right.

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I'd call this one the broad aggregator. It pulls

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from a much wider net. Community stuff like Reddit,

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Quora, even video snippets from YouTube. So for

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Google's AI, you need to be in more places. Yeah,

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content on multiple platforms directly answer

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questions people ask in those communities. Video

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helps too. And the third one? Perplexity. Think

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of this as the expert curator. Perplexity loves

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specialized review sites, detailed technical

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documentation, deep dive analyses. If you want

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to satisfy perplexity, you need specifics, data,

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benchmarks, really detailed comparisons. Whoa.

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Okay. That's that's a lot. It sounds less like

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writing an article and more like building, I

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don't know, content architecture layered three

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ways deep. Yeah. I mean, imagine trying to scale

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that structure to satisfy like a billion different

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queries across three systems that want fundamentally

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different things. It's intense. It really means

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you can't just write one blog post and, you know,

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hope it works everywhere anymore. So does Argyr

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more about how well the content is structured

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for it to pull out info or is it just about the

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overall authority like the source? Oh, structure

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is absolutely key. RAG actively looks for formats

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it can read easily. Clear, defined content makes

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for a much better ingredient in its synthesis

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process. Okay, so if RAG needs this highly structured

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AI readable stuff, we need a plan, a concrete

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plan. How do we actually do that? How do we restructure

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content? Right. This brings us to the AG framework.

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It's basically four steps to make your content

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AI ready, but critically still engaging for actual

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humans. Okay. Four steps. Let's hear them. Step

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one, hook the humans, but scaffold it for the

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AI. This means every important piece of content.

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It must start with the TLDR box. Too long, didn't

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read. Right. The TLDR gives the human reader

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instant value, which is great. But for the AI?

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For the AI, it provides structured, citable facts

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right at the top. Super easy for it to pull out.

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And crucially, right there near the top, you

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have to display your authority signals, author

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credentials, expertise. Don't bury them. Okay.

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TLDR and authority up front. Step two. Step two.

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Build atomic answer blocks. Stop writing long,

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rambling essays. Think of your content as a collection

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of standalone, answerable units. The structure

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here is pretty much non -negotiable, and each

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two -header framed as a specific question. right

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below it, a direct answer. Then follow that with

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a key data point or evidence and cite your source

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if possible. Atomic blocks. So the AI can just

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cherry pick the one specific bit it needs for

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a particular query. Makes sense. If the answer

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is buried deep in a long paragraph, the AI might

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just skip it. Exactly. You know, I still kind

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of wrestle with prompt drift myself sometimes,

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especially trying to nail that TLDR box just

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perfectly for extraction. It's genuinely hard

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work to distill deep insights into... like three

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bullet points that actually capture everything.

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Yeah, I can imagine. Okay, step three. Step three,

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add evidence and structure. AI loves clear structure

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because it's predictable, reliable. So use comparison

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charts, data tables, step -by -step processes,

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really lean into those. The sources we looked

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at also emphasized using the before -after scenario

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structure. Ah, like showing the impact. Yeah,

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illustrating that shift you mentioned earlier,

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like we had 12 ,500 visitors converting at 2

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.1%. Now we have 9 ,800 converting at 4 .7%.

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Specific comparable data is highly citable. Got

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it. Concrete evidence and the last step. Step

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four, layer in those authority signals. We mentioned

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putting them up front, but you need them woven

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throughout too. This is EEAT. Experience, expertise,

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authoritativeness, and trustworthiness. Think

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of EEAT as the AI gatekeeper's main checklist.

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Use specific language that signals experience

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like, in our internal testing across 500 campaigns,

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or based on my direct experience running X for

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five years. reference external reports for authoritativeness.

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Right. Prove it. Don't just claim it. Okay. So

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on EET, what's the element authors most often

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neglect when they try to apply this framework?

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It's usually experience. They tell you what they

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know, but they totally fail to show how they

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learned it. You need that proof of work, those

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specific examples. Okay. Knowing the theory is

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one thing, but putting it into practice needs

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a clear plan. The sources laid out a kind of

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30 day ago optimization plan, right? Focused

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on thousands. Yeah. Pretty straightforward. Week

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one is audit. Find your top, say, 10 high -value

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topics. Then critically analyze how ChatGPT,

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Google AI, and Perplexity are answering questions

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about those topics right now. See what sources

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they're using. Okay, audit first, then. Week

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two is create. Take that high -value content

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you identified and rewrite it using the full

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Ikigo framework we just discussed. TLDR box,

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atomic blocks, structured evidence, EET signals.

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And the final phase? Week four is measure. This

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is where you intentionally shift your metrics.

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Get away from vanity metrics like raw traffic

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volume. Focus on what actually matters now. Which

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brings us to the new metrics. These are how we

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track if this ego stuff is actually working.

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Exactly. You need to track AI citation frequency.

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How often is your content explicitly linked or

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cited by the AI? That's GEO success. Okay. Then

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AI referral traffic quality. Yeah. What are the

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actual conversion rates of the visitors the AI

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does send you? Are they really 4 .4 times more

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valuable? And a third. And the brand mention

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rate. Even without a direct link in that specific

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answer, how often is your brand just named as

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a solution? That's ego success. That authority

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is the new gold. Right, becoming part of the

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AI's knowledge base. Okay, let's quickly touch

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on mistakes to avoid. What trips people up? Number

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one biggest mistake. Optimizing only for one

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AI system. You build great stuff for ChatGPT's

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preferences, but ignore Google AI or perplexity.

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You're limiting your reach massively because

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of those different personalities. Okay, don't

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put all your eggs in one AI basket. Mistake two.

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Neglecting the human reader. Don't make your

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content so rigidly structured that it sounds

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like a robot wrote it. It has to serve both AI

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extraction and genuine human engagement. It's

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a balance. Good point. And number three. Hiding

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your credentials. Burying the author bio, not

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stating expertise clearly up front. Remember,

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AI needs those EET trust signals immediately.

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Don't make it hunt for them on some buried about

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us page. Makes sense. So besides just not hiding

00:12:22.779 --> 00:12:24.720
credentials, what's one quick, immediate fix

00:12:24.720 --> 00:12:26.799
most businesses could probably make in that first

00:12:26.799 --> 00:12:29.940
audit week to boost their EET signals? Be specific

00:12:29.940 --> 00:12:32.779
with dates and sources. Instead of saying studies

00:12:32.779 --> 00:12:36.460
show, say, a 2024 Gartner report found, include

00:12:36.460 --> 00:12:39.039
dates on your own data, like in our Q3 testing.

00:12:39.940 --> 00:12:42.000
Specificity builds trust and authoritativeness

00:12:42.000 --> 00:12:44.740
quickly. Hashtag tag tags ultra -crime. Okay,

00:12:44.799 --> 00:12:47.220
let's bring it all home. The big idea that really

00:12:47.220 --> 00:12:49.740
ties all this together, traditional SEO, that

00:12:49.740 --> 00:12:53.139
was a fight for clicks. This new game, GEO and

00:12:53.139 --> 00:12:55.539
a Go, it's fundamentally different. It's about

00:12:55.539 --> 00:12:58.059
becoming the trusted go -to source that AI systems

00:12:58.059 --> 00:13:01.230
actively cite and recommend. and the advantage

00:13:01.230 --> 00:13:04.309
this framework gives you a huge head start while

00:13:04.309 --> 00:13:06.250
your competitors are maybe still chasing those

00:13:06.250 --> 00:13:08.470
vanishing raw traffic numbers you're positioning

00:13:08.470 --> 00:13:10.450
yourself to capture the highest value users the

00:13:10.450 --> 00:13:12.110
ones who actually convert you know the question

00:13:12.110 --> 00:13:14.450
really isn't if ai search will dominate everything

00:13:14.450 --> 00:13:16.149
it pretty much already is the real question is

00:13:16.149 --> 00:13:18.429
will you be the source it recommends when it

00:13:18.429 --> 00:13:20.590
does so here's your challenge your takeaway from

00:13:20.590 --> 00:13:23.129
this deep dive choose one core topic that's really

00:13:23.129 --> 00:13:25.389
important to you or your business create your

00:13:25.389 --> 00:13:28.710
first ago optimized asset for it build that tldr

00:13:28.710 --> 00:13:31.429
box structure those answer blocks layer in the

00:13:31.429 --> 00:13:35.429
EAT and then actively test it go ask chat GPT

00:13:35.429 --> 00:13:37.409
perplexity Google AI overview questions related

00:13:37.409 --> 00:13:39.629
to your topic see if your content starts showing

00:13:39.629 --> 00:13:41.970
up see if you get cited that's the path forward

00:13:41.970 --> 00:13:43.710
out to your own music begins
