AI Visibility: GEO, AEO, AI Search & SEO
AI Visibility is a podcast about how businesses get discovered, trusted, and chosen in the age of AI. Hosted by the team at RiseOpp, each episode explores the strategies shaping modern visibility, including SEO, GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), AI Search, content strategy, marketing automation, authority building, and sustainable growth.
Whether you're a founder, marketer, agency leader, or growth-focused executive, you'll gain practical insights into increasing visibility across Google, ChatGPT, Perplexity, AI Overviews, and the evolving search landscape.
This podcast features research-driven discussions, expert analysis, and actionable frameworks designed to help businesses improve discoverability, build authority, and stay ahead as search and digital marketing continue to evolve.
AI Visibility: GEO, AEO, AI Search & SEO
Why On-Page SEO Strategies Now Need Intent and AI | RiseOpp
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Full Transcript: On-Page SEO Strategies and Tactics for Marketers
On-page SEO has moved beyond keyword placement into a system for matching search intent, technical quality, and AI-driven discovery.
This episode breaks down how On-Page SEO Strategies use semantic mapping, topic clusters, Core Web Vitals, internal linking, structured data, and schema markup to improve visibility.
Marketers, founders, SEO professionals, and growth leaders will learn how to align technical optimization with useful content and long-term organic growth.
👉 Read the full guide:
https://riseopp.com/blog/on-page-seo-strategies-and-tactics-for-marketers
Welcome to a new deep dive. Today, uh, we're looking at a stack of sources to figure out how to survive the rapid evolution of on-page SEO. We've got fresh data from SEMrush, RIFS, and Digital Silk. And well, back in the day, optimizing a page felt a bit like stuffing a turkey.
SPEAKER_00Aaron Powell Right, just cramming it all in.
SPEAKER_01Exactly. You just crammed as many keywords as possible into the text, you know, and hoped for the best. And getting it right still matters because organic search drives a massive 53% of all website traffic. That's from the digital silk data. But uh that old stuffing playbook, totally obsolete.
SPEAKER_00Aaron Powell Oh, completely gone. Now, optimizing your site is, I mean, it's more like hosting a dinner party. And your VIP guest is an AI algorithm.
SPEAKER_01Aaron Powell Okay, let's unpack this. How do we cater to this new AI guest without ruining the experience for human readers?
SPEAKER_00Aaron Powell Well, we really have to start treating modern SEO as a marketing operating system rather than just a mechanical checklist. Right. Search engines and AI models like Gemini and ChatGPT, they aren't just scanning text for keyword matches anymore. They are mapping semantic user intent.
SPEAKER_01Aaron Powell So they're looking for context.
SPEAKER_00Aaron Ross Powell Exactly. They analyze the relationships between words and look at behavioral signals, things like previous searches or geographic location, just to understand the underlying problem you are trying to solve.
SPEAKER_01Aaron Powell So instead of just looking for the exact phrase like best running shoes, the model calculates that a user is probably looking for trail running shoes because of their recent search history about hiking.
SPEAKER_00Aaron Powell Spot on.
SPEAKER_01Right, zero click because users are getting their answers synthesized directly on the page, right?
SPEAKER_00Yeah, exactly. The Sumrush data actually found that over 13% of Google searches now include AI-generated summaries. And uh 88% of those are triggered by informational queries.
SPEAKER_01Wow.
SPEAKER_00Yeah. So the engine just reads the web, writes the summary, and the user never even needs to leave Google.
SPEAKER_01Aaron Powell Wait, I have to challenge this whole strategy for a second, though. If the AI just answers the question immediately on the page, don't we lose the traffic? Like the a refs report in our stack shows the top organic link loses over 34% of its clicks when an AI overview appears.
SPEAKER_00Aaron Powell It's a huge hit for sure.
SPEAKER_01Right. If I'm losing a third of my clicks right off the bat, why even bother optimizing?
SPEAKER_00Well, that drop in traffic is exactly why this force is a complete pivot in our strategy. The central metric of success is shifting, you know, away from standard click-through rates. Now it's all about citation frequency.
SPEAKER_01Citation frequency, like getting mentioned.
SPEAKER_00Yeah. If we can't guarantee the click, our goal is to become the AI's source material. We want the language model to quote our declarative statements directly and link back to us as the origin of that information.
SPEAKER_01Oh, I see. But if we need them to quote us directly, it sounds like we need to feed the AI our credentials in a language it natively understands rather than just, you know, writing a good article and hoping it extracts the right data.
SPEAKER_00Aaron Powell Which brings us to schema markup. This is basically what translates your human content for algorithms by wrapping your text in invisible code tags.
SPEAKER_01So you are specifically tagging a string of text as author or FAQ or whatever.
SPEAKER_00Exactly. Or product review. That way the AI doesn't have to parse natural language to guess if a name belongs to a writer or just some person mentioned in a quote.
SPEAKER_01It's basically using the Dewey Decimal system for your website. You're handing the AI a perfectly categorized map of your article before it even reads it. Like, here are my credentials, here's the main takeaway, and here's the data.
SPEAKER_00Aaron Powell That is a great way to put it. And algorithms demand that structural map because they are looking for EET, you know, experience, expertise, authoritativeness, and trustworthiness.
SPEAKER_01Right, the acronyms.
SPEAKER_00Yeah. They need literal proof of experience. So when your schema metadata points directly to verifiable authors, custom data, and original research, you prove a credible human wrote the content. And that naturally elevates your trust score in the model's eyes.
SPEAKER_01So whether you run a personal blog or a massive e-commerce site, your new mandate is what the sources call data-driven creativity. You have to write compelling stories for the human, but tag everything structurally for the machine.
SPEAKER_00Application is everything here. You have to blend the technical framework of schema with an authentic human voice. That ensures the algorithm can validate your expertise while the reader, you know, actually enjoys the content.
SPEAKER_01That makes total sense. But here is where it gets really interesting and maybe a little unsettling to think about. If AI systems rely so heavily on this structured schema data to decide which human experts to cite, will we soon reach a point where AI models start generating their own structured data?
SPEAKER_00Oh, like just to cite other AIs.
SPEAKER_01Yeah. Could we see a future where human creators are cut out of the discovery loop entirely, just algorithms talking to algorithms? Definitely something to ponder as we wrap up today's deep dive.