Local SEO Unlocked

Is SEO Really Dead? The Rise of AIO and What It Means

• Don Phelps • Season 1 • Episode 16

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Artificial Intelligence Optimization (AIO) is fundamentally changing online visibility, with 13% of Google queries already showing AI overviews rather than traditional search results. We explore what still works, what doesn't, and how to get your content recognized and cited by AI systems in this new search landscape.

• Technical excellence remains essential – fast, accessible sites provide clear signals for AI tools
• Topic clustering and comprehensive content demonstrate authority to AI systems
• Clear writing that directly answers questions is critical as "LLMs are voracious readers but picky eaters"
• Schema markup functions as your site's "organized resume" for AI, helping it understand relationships
• FAQs and how-to formats serve as "LLM fuel" due to their modular, digestible structure
• Keyword stuffing and content created for algorithms rather than users is now "dead on arrival"
• Focus on intent clusters instead of keywords to build content ecosystems around user needs
• Target specific, scenario-based queries that match how people actually ask questions to AI
• Structure content with question-based headings followed by direct, citation-ready answers
• Use AI tools to reverse-engineer what gets cited and run visibility tests with your key terms

Start experimenting today with these AIO techniques – the brands that win will be those who understand how LLMs think and structure content to consistently earn a place in AI answer boxes.


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Speaker 1:

Welcome to the Deep Dive. We're here to take that pile of sources you've got and turn it into clear, actionable insights for you. Today, we're digging into something that's really changing the game for online visibility artificial intelligence optimization you might hear it called AIO. We've got some fascinating material lined up, including insights from Don Phelps, and really our mission for you today is to cut through all the noise. We wanna figure out what still works, what really doesn't anymore and what you actually need to do to win in this new AI search era.

Speaker 2:

Yeah, it's a really critical conversation to be having right now. I mean think about this as of the first quarter of 2025, over 13% of Google queries. They're already showing AI overviews.

Speaker 1:

Wow, 13% already.

Speaker 2:

Exactly so. We're clearly moving away from just lists of links, those traditional results, towards what some of our sources are calling curated conversations.

Speaker 1:

Curated conversations. I like that. So if you're looking to, you know, really get your content not just found but actually recognized and maybe even cited by AI, this deep dive is definitely for you. Now, I think it's easy to assume AIO is just, you know, seo with a bit of AI sprinkled on top.

Speaker 2:

Right.

Speaker 1:

But the sources we've looked at, they're pointing to something much bigger a real strategic mindset shift.

Speaker 2:

That's spot on. And what's really interesting is, yeah, AIO absolutely rewards a lot of the SEO best practices. We already know Things like technical health, good content, but those things they're now, as one source puts it, table stakes, not differentiators. They're just the baseline. You need to even play.

Speaker 1:

Table stakes. Okay, so what's the core difference then?

Speaker 2:

Well, the core difference is this In traditional SEO, you're mostly trying to get found in that list of blue links. Right In AIO, you're essentially auditioning for a quote. You want the AI to pick your content to feature in its answer.

Speaker 1:

Auditioning for a quote. That really changes the perspective, doesn't it? It's not just about ranking on the page, Not anymore. It's about getting your stuff recognized by the AI system so well that it actually shows up in the answer when people ask questions.

Speaker 2:

Precisely. And that brings us to okay, what does still work, what are those foundational things, the non-negotiables that still matter?

Speaker 1:

Right the table stakes.

Speaker 2:

Exactly. Our sources point to about five key areas. First up, technical excellence your site still needs to be fast loading, mobile, optimized, easy for search engines. And now AI is to crawl. It's critical.

Speaker 1:

Why is that still so important for AI? Specifically?

Speaker 2:

Well, because AI tools aren't just reading text, they're parsing structure, understanding context. Clean, fast sites have less noise, more signal for them. They just, you know, they prefer sites that are fast and functional. Makes their job easier.

Speaker 1:

Okay, makes sense. Remove the friction for the AI. What's second?

Speaker 2:

Second is topic clustering. If you've already invested time in building out pillar pages, topic clusters, strong internal linking, you're actually in a good spot.

Speaker 1:

Ah, so that work wasn't wasted.

Speaker 2:

Not at all AI tools, especially these LLMs large language models. They really prefer comprehensive resources that show topical depth. Think of it like this the AI wants one hub, not a mess of scattered thoughts. It helps them see you as an authority.

Speaker 1:

Yeah, I can see how an AI would rather pull from one solid source than try to piece things together from all over the place. Absolutely.

Speaker 2:

Third is clear writing that answers questions. This sounds basic, but it's key. Llms are described as voracious readers, but also picky eaters. Content that's genuinely written well, aiming to teach or explain something clearly to a human. That works just as well for AI.

Speaker 1:

So good writing is good writing, whether for a person or an AI.

Speaker 2:

Pretty much. If a human can easily get the answer, chances are an LLM can too. Fourth schema markup Structured data.

Speaker 1:

Ah, schema Always important, but maybe more so now.

Speaker 2:

Definitely more so. It's foundational. Think of it like your site's highly organized resume for the AI Schema helps LLMs understand what your content is about, not just the words it contains. One source called it one of the clearest signals LLMs rely on. It helps them map out relationships between things.

Speaker 1:

So you're basically giving the AI a clear index telling it this is a recipe, this is a product, this is a how-to guide.

Speaker 2:

That's a perfect way to put it. And finally, number five FAQs, how-to, guides and lists these formats. They're like LLM fuel.

Speaker 1:

Why they're specifically.

Speaker 2:

Because they're naturally modular. They're digestible. Ai tools tend to lean heavily on these formats when they need to summarize information or pull out specific points or steps to cite. So if you're already creating answer-ready content like that, you're basically already speaking the language of AIO.

Speaker 1:

Okay, so those are the foundations that still hold strong. Let's flip it then. What about the tactics that maybe they worked a few years ago, but now are just well ineffective, or maybe even invisible to AI?

Speaker 2:

Right, and this isn't about you know, throwing out your entire playbook, but it's really crucial to know which Flays just aren't going to work anymore. First big one Keyword stuffing without intent. Llms are smart. They aren't fooled by just like a pile of terms duct taped to a blog post, as one source colorfully put it. Okay, If your content only exists to try and rank for a term and not to actually help someone, the AI is not buying it.

Speaker 1:

So that whole era of writing thin content just to hit a keyword density number that's really over now. Oh, absolutely.

Speaker 2:

Which leads to the second point content for the algorithm, not the user. Remember those like 500 word fluff pieces targeting best email platform 2024?

Speaker 1:

Yeah, we've all seen them.

Speaker 2:

Our sources are pretty blunt and they're DOA and AIO dead on arrival. Ai search tools are actively looking for the most complete, helpful and well-structured content, not just keyword filler.

Speaker 1:

That feels like a significant shift, even from just a couple of years back in SEO.

Speaker 2:

It really is. Third thing that's less effective chasing head terms, you know, trying to rank for those huge broad terms like CRM or SEO the old holy grail, Exactly. But AI tools now, they much prefer long tail contextual queries. Something like best CRM for solo founders with no sales team.

Speaker 1:

Yeah.

Speaker 2:

The broader the term, the harder it is for the AI to give a truly useful, specific answer. So it leans towards specificity.

Speaker 1:

So it's less about casting that super wide net and much more about precision targeting.

Speaker 2:

Precisely Number four blind backlink chasing. Now, backlinks aren't totally irrelevant, let's be clear.

Speaker 1:

Okay.

Speaker 2:

But AI search seems to be more interested in what you say, how clearly you say it, and whether other credible sources actually reference and validate it. Authority isn't just a numbers game of how many links you have anymore. It's more about demonstrated expertise and genuine trust signals.

Speaker 1:

That's a big change. It puts way more emphasis back on the actual quality and relevance of the content itself.

Speaker 2:

It really does. And the fifth point here is ignoring tone and context. This is interesting. Lms don't just read the words, they analyze how things are said. If your brand's tone comes across as like robotic or the messaging feels off for the user's actual question, you might not just get skipped over.

Speaker 1:

You could get misquoted.

Speaker 2:

Yeah, or maybe cited in a context that doesn't actually help your brand. The AI might misunderstand or misrepresent your point if the tone isn't right.

Speaker 1:

OK, so if those are the shifts and the things to avoid, what does it actually take to show up effectively, to show up well, in this AI discovery layer? What's the new playbook look like?

Speaker 2:

Yeah, this is the crucial part, isn't it? How do we adapt for what one source called user empathy at scale? The first rule in this new playbook seems to be thinking intent clusters, not just keyword clusters.

Speaker 1:

Intent clusters. Okay, what does that mean exactly?

Speaker 2:

It means forgetting about just stuffing keywords. Aio needs a much deeper dive into why someone is asking a question, what's their underlying goal, and then you build whole content ecosystems around those intents. So for A-B testing you don't just have one page. You'd have say what is A-B testing? Then maybe how to run an A-B test in Klaviyo, a-b testing ideas for e-commerce, maybe even what to do when your A-B test fails.

Speaker 1:

Each piece tackles a specific angle of that core intent. That makes sense. You're providing comprehensive coverage without making one page impossibly long, and you're signaling to the AI hey, we really know this topic inside and out.

Speaker 2:

Exactly Builds authority. Second tactic target long tail scenario-based queries. Generic is out, context is definitely in. So instead of just email marketing tips, you'd aim for something much more specific, like how do I improve open rates in Gmail versus Outlook, specifically for B2B emails?

Speaker 1:

Wow, that's ultra specific.

Speaker 2:

It is and it sounds exactly like something a real person would actually type or ask an AI. Right, You're meeting a very precise need.

Speaker 1:

Yeah, you're anticipating how someone would genuinely ask for help in a real situation.

Speaker 2:

Precisely. Third, use headings as questions and answer them clearly. Think modular LLM skim. They look for structure when your H2 heading directly matches a likely user query like how do I increase my email open rate and outlook?

Speaker 1:

Instead of something vague like improve your email strategy.

Speaker 2:

Right and then the paragraph right below it gives a clear, concise answer. You make it incredibly easy for the AI to just grab that section and cite you.

Speaker 1:

Get straight to the point for the AI, but that also makes it clear for the human reader too. Win-win.

Speaker 2:

Absolutely. Fourth point structure content for AI tools. This is where formatting really matters. Things like bullet points, numbered lists, step-by-step instructions, good internal linking LLMs apparently eat this stuff up. Also include clear definitions, good examples, maybe subtle clarifiers. These things make your content very quotable for an AI.

Speaker 1:

So it's not just the writing, it's how you present the information, making it super digestible, AI friendly.

Speaker 2:

That's a huge part of it. And fifth, maybe the most important account for the human behind the query, when you really optimize for the user's actual mindset, you know, are they short on time, are they budget conscious, are they skeptical? When you address that our sources suggest, you don't just rank, you resonate, you build actual trust.

Speaker 1:

Okay, resonate, I like that. Now you mentioned AI tools. Think differently. This is where it gets really interesting, right, how search intent itself is shifting.

Speaker 2:

Yeah, this is a big one. Ai doesn't just answer faster, it approaches the type of answer differently. We used to talk about traditional search like a buffet of links. Right, you pick what looks good. Ai search is more like getting one plate, one answer curated for you. One plate, okay. So how does that change intent? Well, the classic intent types informational, transactional, navigational. They're still relevant, yeah, but our sources are really emphasizing two additional types that seem to carry a lot more weight for LLMs instructional and scenario-based.

Speaker 1:

Instructional and scenario-based. Why are those so important now?

Speaker 2:

Because they signal really high intent.

Speaker 1:

Yeah.

Speaker 2:

And they provide rich context. Someone asking an instructional how do I? Or scenario-based what's the best? X for Y situation query they're usually ready to do something or make a decision. That's where the money is potentially.

Speaker 1:

And there's data backing this up, isn't there Something from SEMrush?

Speaker 2:

Yeah, exactly Our sources mentioned. Semrush found that when Google's AI overviews, search, gpt or active standard informational queries, plummeted from like 81% down to about 39% and get this, 70% of queries suddenly fell into this unknown bucket because they didn't fit the old models. Neatly, 70%. But that unknown bucket, that's not a problem, it's the opportunity. It's full of those neurons, context-rich, help-me-decide type questions that AI is perfectly suited to answer.

Speaker 1:

Okay, so this changes how we need to approach optimization, which leads us to the AIO process, itself described as speed dating with robots.

Speaker 2:

Huh yeah, that's a memorable way to put it, because you really might only get one quick shot to make an impression and get cited. So the process needs to be sharp. Step one do smart query research. Forget just looking at keyword volume. You need to understand how real people actually ask questions in AI chat interfaces.

Speaker 1:

How do you do that effectively?

Speaker 2:

Well, one great pro tip from the sources is actually ask to chat, GPT or similar tool. Ask it. How would a beginner ask about your topic? You get instant insight into natural language queries.

Speaker 1:

Oh, that's clever. Use the AI to understand how people use the AI.

Speaker 2:

Exactly Step two. Map intent like a human Really figure out. Is this person trying to learn something new? Compare options fix a problem. Are they ready to buy? The examples given were great. What is schema markup? That's clearly informational. Schema markup versus meta tags that's consideration. How to add schema in Shopify definitely instructional. Best plugin for schema markup. They're likely purchase ready, knowing that intent shapes everything.

Speaker 1:

Okay, mapping the real goal.

Speaker 2:

Right Step three craft clear, modular answers. This is critical. Write in a way that an AI can basically copy paste your answer without needing to rewrite it. That means one question, one clear answer, short paragraphs. Use those bullets and numbered steps, and absolutely no throat-clearing intros or clever detours. Get straight to the point. You're not telling a story, you're solving the user's immediate need.

Speaker 1:

Direct concise structured yes.

Speaker 2:

Step four Monitor and improve. Aio isn't something you set up once and walk away from. You have to track it. Are you getting cited in LLM responses? What's the tone like when you are? Where are your competitors showing up?

Speaker 1:

Active monitoring is key.

Speaker 2:

Absolutely. Step five optimize the tech. We mentioned technical excellence earlier Page speed, mobile crawlability, schema they all still matter, but the focus shifts slightly. It's about how easily machines can interpret your page specifically in the context of a query. And step six structure like a machine learner would want.

Speaker 1:

Structure like a machine learner? Okay, yeah.

Speaker 2:

LLMs don't browse visually like humans. They parse data to make it super easy for them. Use headings that are full questions. Include definitions and examples. Clearly Use specific schema types. How-to QI page article that explicitly tell the AI the purpose of your content. Break answers into logical chunks. It's all about making it machine readable. The sources stress this whole process requires discipline.

Speaker 1:

Discipline. Okay, that makes sense. Now, doing all this, it probably requires different tools than we might have used for traditional SEO. Right, this isn't a game for tools built back in 2015. What are some of the interesting players emerging in this AIO space?

Speaker 2:

Yeah, the tool landscape is definitely evolving. Our sources mentioned a few interesting ones. There's Peak.

Speaker 1:

Peak.

Speaker 2:

Yeah, P-E-C. Apparently, it helps you see exactly where and how your brand is getting mentioned in AI answers across ChatGPT, Gemini, Perplexity, those kinds of platforms. It basically turns that AI blind spot into a measurable scoreboard.

Speaker 1:

Okay, visibility tracking for AI answers. That sounds useful.

Speaker 2:

For sure. Then there's Athena. This one seems focused on competitive intelligence within AI search, so seeing who's really owning which types of queries in the AI results.

Speaker 1:

Competitor analysis for AI. Oh God.

Speaker 2:

Goodie. This tool is designed to help marketers actually optimize their content for AI results. Competitor analysis for AI oh good Goodie. This tool is designed to help marketers actually optimize their content for AI engines. It looks at things like tone, structure, scheming, use and gives recommendations based on how AI seem to be behaving.

Speaker 1:

So more on the content optimization side.

Speaker 2:

Exactly. And then, of course, you have established players evolving. The Semrush AI toolkit was mentioned. It's extending their traditional SEO tools into this new territory, things like tracking your AI visibility, analyzing the sentiment around your brand in AI mentions.

Speaker 1:

Sentiment Like is the AI describing your brand as expensive or easy to use?

Speaker 2:

Precisely that kind of thing, Plus suggesting topics tailored specifically for those AI-style long-tail queries we talked about.

Speaker 1:

Okay, so there are tools emerging. It sounds like the key takeaway here is, like one source said, the best tool is the one that closes your current gap. Whatever you need most right now. That seems right, but the worst move is just ignoring this whole AI layer completely.

Speaker 2:

Yeah, ignoring it is definitely the only wrong move. This AI discovery layer it's already shaping how people perceive brands and make purchase decisions. Action is really needed now.

Speaker 1:

So let's bring it home. What are the concrete strategic moves people listening can start making, like today or this week, to actually begin winning in AIO?

Speaker 2:

Okay, actionable steps. First, shift your strategy to intent clusters. Stop thinking article by article. Start thinking ecosystem. Build those networks of content around core user needs, Like the example pillar topic what is marketing attribution Supported by best tools for B2B attribution? How to explain attribution to your CFO? Common attribution mistakes. Doing that trains the AI to see you as the comprehensive, trustworthy source.

Speaker 1:

Building that web of expertise makes sense.

Speaker 2:

Second, use AI tools to reverse engineer AI behavior. Be proactive. Go into ChatGPT or Gemini yourself. Type in your key terms, your customer questions, see who gets cited. Look at the structure of the content that gets pulled. Then go back and improve your own stuff based on that recon.

Speaker 1:

Use the AIs to learn from the AIs.

Speaker 2:

Exactly. Third, get specific, get real. Generic just doesn't cut it anymore. Don't write how to increase website traffic. Write how to drive traffic to a Shopify store without using paid ads. Loms seem to prefer answers that sound like they were written for a person, not for a playbook. That specificity signals relevance.

Speaker 1:

It feels more authentic too, like you're answering a real question.

Speaker 2:

It does. Fourth, and this is a quick win, run a five-minute AI visibility test. Seriously, just take five minutes. Type your brand name, your main product, your top competitors, maybe your top three customer questions into chat. Gpt, gemini perplexity. See what comes up. Are you mentioned? What's the tone? Who is showing up? The sources are clear. If you're not showing up, the work starts now.

Speaker 1:

That's a really simple eye-opening exercise anyone can do right away.

Speaker 2:

Totally. And fifth pilot measure repeat Don't feel like you have to overhaul everything overnight. Start small, pick maybe five key pages. Restructure them using this AIO process. Add the right schema, rewrite the headings as questions, use bullet points, then monitor if they start getting cited more in AI tools. If it works, scale it up. If not, adjust your approach. The key is, as the source said, but don't wait.

Speaker 1:

Don't wait, start experimenting now. Pilot measure repeat Okay, so wrapping this all up. What does this really mean for you, the listener? It sounds like AIO isn't just some side quest or passing fad.

Speaker 2:

Not at all. It really is the next evolution of SEO. It's where things are headed.

Speaker 1:

And the brands that are going to succeed.

Speaker 2:

The brands that win will be the ones who take the time to understand how these LLMs actually think, what real users are truly asking, and then figure out how to structure their content so it consistently earns its place in that AI answer box.

Speaker 1:

Not just landing somewhere in the link pile, exactly Getting into the curated answer. So you don't need to throw out everything you've learned about SEO and online visibility.

Speaker 2:

No, definitely not. The foundations are still important.

Speaker 1:

But you absolutely have to evolve how you apply that knowledge in this new context and the payoff if you get it right. Our sources suggest you don't just show up.

Speaker 2:

You get quoted, you get trusted, you get chosen. It's about becoming the AI's preferred source, which ultimately means becoming the user's preferred answer.

Speaker 1:

That's powerful, get quoted, trusted, chosen.

Speaker 2:

Which leaves, I think, one important question for everyone listening to consider Are you ready to make AI work for your brand and not the other way around? Are you ready to adapt?