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Welcome back to Conquer AI Search, your essential guide for navigating this crazy, fast-moving world of AI search. I'm Katherine and I'm here with my colleague from the AI Monitor team. Great to be here.

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So we're on this mission together, right? Equipping you with the top 11 most effective generative engine optimization techniques. GEO, or you might know it as AI Optimization. We've already covered six really crucial strategies.

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Things like LLMs.txt file, using Reddit, authoritative citations, evolving SEO, the importance of PR, and readability. That's right, a lot of ground covered. Exactly.

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So today we're jumping into technique number seven. How to actually create quality content that AI systems recognize to boost your GEO or maybe answer engine optimization, AEO. And this isn't just, you know, ticking boxes for algorithms.

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It's really about making your content genuinely valuable, especially now in this AI-first landscape. You've really hit on something key there. For like the longest time, quality content just felt like this vague buzzword, didn't it? Totally, yeah.

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But now, with things like AI overviews and these generative engines really shaping search results, it actually has, you know, real concrete implications for your visibility. It's a fascinating shift, honestly. And we've pulled together some pretty powerful insights today from top content strategists, market data, recent research.

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Should be good. Okay, let's unpack that then. When we say quality content now with AI in the mix, what does that actually, you know, look like? What does it mean? Well, at its heart, right, quality content always needs to do two things.

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Help your audience and help your business. That hasn't changed. It could be a blog post, a video, whatever.

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But specifically thinking about AI and search, and let's be honest, mostly Google's influence here, quality content is really tightly linked to their EEAT guidelines. Ah, EEAT, right. Remind us what that stands for again.

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Yeah, it's experience, expertise, authoritativeness, and trustworthiness. So Google's saying very clearly they want creators who show they have firsthand experience, real expertise, or they seem as reputable, a trusted source. And fundamentally, is the page itself, you know, accurate, honest, safe, and reliable? They even have actual humans, these search quality raters who manually check websites.

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Wow, okay. Yeah, it's to make sure their algorithms are actually promoting helpful, reliable, genuinely people-first content. It's a huge signal.

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Write for people first. Don't just try to game the system. Okay, so it really boils down to genuine value for the human reading it.

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But why is this specific focus so critical, like right now, for websites and businesses? Because without it, honestly, your site just won't pull in as much traffic, especially organic search traffic or answers that get generated by AI tools like ChatGPT. The more quality stuff you have, the more shots you have at ranking, gaining influence, and importantly, building trust with your audience. You know, a strong online presence filled with valuable content, that fosters that connection.

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And I assume that connection then feeds directly into actual business goals. Oh, absolutely. Quality content, ultimately, is what drives traffic.

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It generates leads. It turns prospects into customers. There's this great example of Noah Greenberg, the CEO of Stacker.

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He became a HubSpot customer five years after first encountering their content, not because of a sales pitch, but because they were just consistently putting out valuable stuff. It really shows the long game aspect of content, building influence over time. That really makes sense, the long game.

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Okay, so if we're looking for actionable steps, the keys to actually writing this quality content now, in the age of AI, where do we start? I know our sources pointed to some really good advice from HubSpot strategists. Yeah, this is where it gets really practical. HubSpot's approach gives a pretty clear roadmap.

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One of their foundational ideas is to organize around topic clusters. Topic clusters, okay. Yeah, the whole idea of just ranking for random keywords, that's pretty much gone.

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Google now heavily figures what they call topical authority. The insight is, go deep. Become the recognized authority on a specific, fairly narrow niche.

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HubSpot did this. They actually split their huge blog into four separate properties, marketing, sales, service, and website. Oh, interesting.

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Yeah, and each one has its own tightly defined topic clusters. They even made the pretty bold move of deleting popular content that wasn't relevant. They had this super popular post on how to type the shrug emoji.

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Ha, I might've read that one. Right. But it got pruned, because it didn't align with their core expertise, even though it got traffic.

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It's all about signaling to Google that they are the authority in their chosen areas. That takes discipline. It does.

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And building on that authority, another huge insight is, lean into your humanity. It's your superpower. Okay, I like the sound of that.

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Yeah, AI can write text, sure, but it can't feel. It doesn't have lived experiences. Your unique perspective, your stories, the authority you've built over time, that's the stuff AI just can't replicate.

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It's your advantage. HubSpot writers are actually encouraged to inject personality, anecdotes. They even ran an experiment they call E-Sperience Soup.

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Experience Soup. Yeah, basically focusing on weaving in personal firsthand experience. And get this, it boosted clicks by something like 724% on one test.

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Wow. So while AI can maybe simulate stuff, it just can't fake that genuine human touch. That's powerful.

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Makes the content feel more real, more trustworthy, too. How does this connect to how people are actually searching now? Directly ties into the next principle. Embrace the AI era by writing for LLM search, large language model search.

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Right, so thinking beyond just Google. Exactly. It's not just traditional SEO anymore.

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You need to think about influencing models like ChatGPT. There's an Elon University study found that two-thirds of LLM users are basically using them as search engines now. Two-thirds? Yeah.

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And HubSpot noticed their SVP of marketing, Kieran Flanagan, had a YouTube video about DeepSeek suddenly appearing in ChatGPT's results. Why that video? Well, because it was early, it went deep into the topic, and importantly, it was on YouTube, which seems to be a pretty strong signal for these LLMs. It tells us that timing, depth, and where your content lives matters more than ever for getting surfaced by AI.

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Timing, depth, platform. Got it. And speaking of AI.

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Right. They also stressed using AI as a catalyst, not a replacement. This is key.

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So how do you use it right? Well, the rule of thumb is, if AI isn't helping you create content faster or better, you're probably using it wrong. For example, Vasha Coleman at HubSpot built an AI agent. It identifies trending topics.

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Turned a four-hour manual weekly task into, like, less than two minutes a day. Nice efficiency gain. AI is brilliant at compiling information, analyzing data, but that human input, that's still essential for, you know, pushing the conversation forward, offering unique takes, applying critical judgment.

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So AI assists, but the human steers the ship. What about actually standing out from all the noise? There's so much content. That brings us to conducting original research.

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This is a huge differentiator. Makes sense. Unique data.

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Exactly. If you have unique data, maybe proprietary insights from your work, or fresh customer perspectives, you can own that space. HubSpot has a dedicated content innovation and research team.

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They're constantly doing surveys for their big industry reports, like this data marketing. That original data, it doesn't just make your blog post better, it becomes lead magnets. And crucially, other authoritative sites cite it, which boosts HubSpot's own authority even more.

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It's a virtuous cycle. That's smart. What else stands out in their approach? Another pretty bold strategy is, dare to give readers a peek behind the scenes.

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Basically practice radical transparency. Ooh, radical transparency. Sounds risky.

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It can feel that way. Few companies really commit to it. But these kinds of posts offer incredibly valuable, real tactical advice.

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HubSpot's blog is kind of famous for breaking down exactly how they achieve successes step-by-step. And even their failures. Like, their CMO openly talked about a blog traffic loss on a podcast.

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That conversation then became one of their most popular blog posts ever. No kidding. Yeah, because that kind of transparency builds massive trust.

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It provides unique, actionable insights you just don't get anywhere else. That level of openness definitely builds credibility. Okay, so they're creating all this great content.

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How do they keep it all fresh and effective? Good question. It's not just about pumping out new stuff. They actually dedicate a huge chunk of their writer's time, like 50 to 80% each month, just to updating old content.

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50 to 80%. Wow. Yeah, because those older pieces, they've aged.

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They've maybe already built up some authority and rank. So, refreshing them with new research, maybe some expert quotes, updated stories, it gives them a whole new lease on life. They found that these updates tend to be most effective for about six to nine months, especially in really fast-moving industries.

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Interesting time frame. And what about the flip side? Content that's not working. Ah, yes, the painful part.

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Prune your low performers. You know the phrase, kill your darlings in writing. It's like that.

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But for content, deleting stuff that isn't performing is actually crucial for staying competitive and focusing your resources. HubSpot has apparently removed thousands of pages after doing content audits. Thousands.

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Yeah, it lets them focus on the content that really aligns with their current strategy. They have a framework for it. Look at the content type, how fresh it is, its organic potential, and then decide.

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Keep it, optimize it, recycle it, or prune it. Keep, optimize, recycle, prune, K-O-R-E-P. Got it.

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Any final big tips from them? Yeah, two more key things. First, the obvious but essential. Keep up with SEO updates.

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The search world changes constantly, so following blogs, social media, thought leaders is just non-negotiable. And second, maybe even more importantly now, diversify and unify your content channels. People aren't just reading blogs anymore, just watching YouTube.

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They're everywhere. Right. Got to meet them where they are.

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Exactly. HubSpot Media really leaned into unifying content across their blog, YouTube, newsletter, podcast. So maybe a YouTube video becomes a podcast episode, which then informs a blog post.

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They call it the video flywheel effect. And the results were pretty stunning. One period, their YouTube views shot up 84% year over year, and leads from YouTube jumped 91%.

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Shows the power of making channels work together. OK, that makes a ton of sense. Now, shifting gears slightly, beyond the content creation itself, you mentioned there's a technical side to optimizing for AI, right? And it's different from old school SEO.

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That's exactly right. It's not about the traditional signals we obsessed over, like backlinks or keyword density so much. It's more about how you structure your content and how you make it visible and understandable to AI crawlers.

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How so? How do these AI search engines work differently? Well, think about ChatGPT, Claude, Gemini, Perplexity, Copilot. They operate fundamentally differently than, say, Google's traditional index. They synthesize information.

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They draw from these massive training data sets, but also access the web in real time. They're prioritizing things like statistical relevance, how often concepts are mentioned together in context, and just sheer clarity. It's a different way of understanding content.

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OK, so technically, how do we make our content ready for that kind of understanding? All right, here's some key technical steps. First, structured data and schema markup. This is huge.

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Like for recipes and stuff. Yeah, but much broader now for AI. Using schema types like how-to, FAQ page, product, article review, video object, breadcrumbs.

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It basically helps AI interpret and summarize your content accurately. It's like giving the AI a labeled diagram of your page. Support content, for instance, often gets cited in AI answers because it tends to be really well structured with things like FAQs.

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Makes sense. Give the AI clear labels. What else? Second, you need to explicitly weave EEAT into your site architecture.

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AI can't guess. Make it obvious. Exactly.

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Display author bios clearly show their credentials. Include expert commentary. Be transparent about your sources.

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Have dedicated trust pages, pricing, security info, support contacts. Make the trust signals visible on the site. OK.

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What about letting the AI bots in? All right. Third is managing your crawl settings and GPT-bot access. You need to make sure the relevant AI bots like GPT-bot for chat GPT, CloudBot, Google Extended for Google's AI stuff, CC-bot for Common Call can actually access your important public content.

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There's this proposed LLM.txt standard, kind of like Robots.txt but for AI training. But honestly, the major models aren't really using it widely yet. So direct bot access through standard controls is still key.

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Good to know. LLMs.txt isn't quite there yet. Number four.

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Fourth, focus on sitemap hygiene and internal linking. A clean, up-to-date XML sitemap and a really strong internal linking structure help these Gen AI tools understand your site's topical authority. How is your content related? Grouping content into those clear topic clusters we talked about really reinforces that authority for the AI.

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Right. Connecting the dots for the AI. What about video? Ah, yes.

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Fifth, optimize your video SEO for AI visibility. This is increasingly important. Tools like Perplexity and Gemini are actively pulling insights, even direct citations from YouTube videos.

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Need good YouTube hygiene too. Absolutely. Search-friendly titles, really detailed descriptions, full transcripts if possible, use timestamps.

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All that metadata is gold for AI trying to understand video content. Okay. Anything else on the technical checklist? Yeah, a few more general but still important technical enhancements.

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Basic stuff but crucial. Improve site speed. Make sure it's mobile-friendly.

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Use canonical tags correctly to avoid duplicate content confusing the AI. Secure your site with HTTPS. And actually monitor your server logs.

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See which AI bots are visiting, how often, what they're looking at. It gives you valuable intel. That's a solid technical list.

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Now, one thing a lot of businesses want is, you know, to show up when someone asks an AI, what are the best tools for X? How do you actually get onto those kinds of AI recommendation lists? Yeah, that's the million-dollar question, isn't it? It's definitely not random chance. These AI models build those lists based on statistical patterns they find in their training data and the live web. So basically, if your brand gets mentioned frequently in the right contexts, associated with solving a particular problem and with clear value propositions, the AI starts to statistically link your brand to that solution.

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So it's about the overall pattern of mentions. Pretty much. Key factors influencing this seem to be.

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Forum credibility AI models really weigh community sources like Reddit heavily. So valuable non-spammy participation there matters. Then there's public social proof conversations on LinkedIn, on X, formerly Twitter.

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AI ingests this public discourse. Sharing value, getting quoted, engaging in industry chats helps. Also, blog and knowledge hub authority, having your own authoritative content builds that contextual relevance.

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And getting mentioned on other industry blogs. Review aggregation is huge too. AI leans heavily on platforms like G2, Captera, Trustpilot.

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Encouraging detailed specific reviews there is vital. And finally, having strong category positioning on your own site. Clearly stating what you solve, who it's for, what makes you different.

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Need to be crystal clear. Okay, so it's mostly about organic signals. Are there any direct ways to influence this? There are starting to be, yeah.

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Perplexity, for instance, has a merchant program where you can actually submit your product catalog. Oh, interesting. And OpenAI has something called the Search Product Discovery Initiative.

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It uses structured web data, remember that schema markup, for product offer review to help it suggest products. Traffic coming from these kinds of AI recommendations tends to be really high intent, often converts well. Good to know there are direct avenues opening up.

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Okay, we've talked a ton about optimizing for AI, but what about flipping it? Using AI to help optimize our own content. Yes, that's a really crucial distinction and a smart way to work. You can absolutely leverage AI tools, things like Surfer, ClearScope, Jasper, or even just prompting ChatGP to your cloud directly.

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How would you use them? For quality assurance, for checking structure, for doing prompt-based clarity checks. Like here's a simple test. Ask an AI tool to summarize your article.

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If the summary completely misses your main point, well, your content might not be clear enough for humans or for other AIs. That's a clever trick. What about all the buzz around AI content detection? People worry about getting flagged.

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Yeah, there's a lot of discussion, especially in places like Reddit communities. The general consensus seems to be don't just ask the AI to write me an essay on X. That often leads to generic detectable output. So what's the better approach? Use AI more strategically.

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Ask it to generate outlines, brainstorm ideas, maybe even help you spot AI-sounding patterns in your own writing that you can then smooth out. AI detectors often look for things like repetitive sentence structures, overuse of certain connector words, a lack of stylistic variation, maybe language that's just too formal or bland. The trick is to consciously infuse human variability, maybe some slight imperfections, your unique voice.

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You can even prompt an AI like rewrite this section in the style of a specific human author to try and make it sound less robotic. Interesting. So use AI as a writing partner, not a ghostwriter.

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Okay, with all these changes, how do we even measure success? The old metrics might not cut it. You're absolutely right. Traditional metrics alone are definitely inadequate now.

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You need to start monitoring a wider range of things. Like what? Okay, so referral traffic directly from AI tools. Conversions you can attribute to AI.

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This might be tricky, but maybe using how did you hear about us. Fields on forms or setting up specific tracking if possible. Watch your branded search volume.

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If more people start searching directly for your brand name, it could be because they were first introduced by an AI. It's like this inverse customer journey AI introduces, Google validates. The inverse journey.

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And obviously track your appearance in AI overviews and gen AI results. You need to be regularly testing relevant prompts and seeing if you show up. Also look for backlinks from AI surface content.

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Some tools generate live links. Monitor your content gap resolution. Are you closing the gaps where AI isn't finding you? Proactively do misrepresentation monitoring.

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If an AI starts hallucinating or saying incorrect things about your brand, you might need to publish correction pages. Yeah, that's a new one, misrepresentation monitoring. And finally, don't forget basic engagement signals on the content you're optimizing for AI.

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Time on page, bounce rate, scroll depth. These still matter to understand if the content is actually resonating. Okay, that's a much broader set of metrics to track.

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So bringing it all together, what does this actually mean big picture? We keep seeing headlines, you know, SEO is dead, isn't... Huh, yeah, not really. Mostly clickbait designed to grab attention. Fangered as much.

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What it really means is that SEO is fundamentally evolving. Look at Google's AI overviews. Yes, they've caused some significant dips in organic traffic for certain sites.

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Conductor saw drops up to 60% on some pages, like 25% fewer sessions for informational content month over month. That's real. Wow, 60% is huge.

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It is. But interestingly, conversions often aren't hit quite as hard, which kind of suggests that maybe some of that previous traffic wasn't super valuable or high intent anyway. So less quantity, maybe better quality traffic.

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Potentially. The absolute key is adaptation. You need to improve your SEO strategy, maybe by prioritizing branded searches more, creating unique content types that AI struggles to replicate, like in-depth reviews, detailed competitor comparisons, really good support documentation, maybe interactive online tools.

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Refine your content strategy itself. Focus more on how and why questions. Leverage your unique first-party data.

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Don't be afraid to have strong, well-supported opinions. And critically, critically, diversify your channel mix. Don't put all your eggs in the Google basket.

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Think PR and newsletters, maybe other search engines, definitely social media, paid ads. Authenticity is going to be paramount, especially in the social platforms getting flooded with generic AI content. You need to stand out.

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So the landscape is definitely shifting, shaking things up, but it sounds less like a death knell and more like a strong call to evolve, to adapt. Exactly. It's the perfect way to put it.

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AI search optimization isn't killing traditional SEO. It's expanding it, adding new layers. You know, those final words of advice from the HubSpot strategist really resonate here.

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Quality content, fundamentally, will always be about serving your audience well. And in this AI-driven world, your humanity, your unique perspective, that matters more than ever, AI has changed the game for sure, but your unique viewpoint, that really is your superpower now. That's a great place to leave it.

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That wraps up today's episode of Conquer AI Search. Thanks so much for tuning in. If you enjoyed the conversation, make sure to follow or subscribe wherever you're listening, whether that's Spotify, Apple Podcasts, Audible, Amazon Music, or right here on YouTube.

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And hey, if you got some real value out of this episode, maybe consider leaving us a rating or a review. It genuinely helps us reach more listeners like you. See you next Saturday with our eighth AI optimization or generative engine optimization technique.

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Welcome, everyone, to the Conquer AI Search podcast. We're part of the AI Monitor team, and I'm Katherine. And I'm Avi.

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Great to be here. Our mission on this show is pretty simple, really. We want to help you boost your visibility in AI searches.

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Right, using straightforward, actionable steps, things you can actually do without needing a huge budget. Exactly. No spending needed for these tips, and, well, we probably shouldn't brag too much.

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Oh, here we go. But we were recently named the number one consultants for generative engine optimization by Yes! Users. That was after their big survey with hundreds of SaaS companies, so feeling pretty good about that.

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Okay. Okay, a little bragging is allowed. It was well-earned.

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We are deep into our 11-episode series now, looking at the most effective ways, you know, the techniques to boost your content's visibility in AI searches. So far, we've covered quite a bit. We've explored implementing those LLMS.txt files, which are, like, super important.

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Yeah, the instruction manuals for the AI crawlers, basically. Exactly. And we've looked at leveraging Reddit, using authoritative citations strategically, evolving your whole SEO playbook for this AI era, and the Power PR public relations.

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Which was surprisingly critical, wasn't it? It really was. So today, we're plunging into the sixth technique, improving the readability of your content to really boost your visibility in generative engine optimization, you know, sometimes called answer engine optimization, or AEO. Yeah, and what's really fascinating here, and this comes straight from our sources, is how much readability, which, you know, we always thought was for making human readers happy, has now become like a cornerstone for AI search visibility.

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It's kind of a paradox. AI systems, they're basically trained on human conversation. So they inherently favor content that's clear, concise, easy for us to process.

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Oh, okay. So it's not just about making your stuff sound nice, it's about making it super digestible for those algorithms. The ones powering AI overviews and those little generative snippets we see? Exactly those.

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Okay, that's a big shift. So let's unpack this. Why now? For someone maybe deep in technical SEO, why is basic readability suddenly more critical? Especially when AI can supposedly crunch through tons of complex stuff? Well, it's kind of because of that processing power, that clarity matters so much.

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Our sources, they really highlight that AI models prioritize content that just screams E-E-A-T. Experience, expertise, authoritativeness, trustworthiness, and transparency, too. And transparency, yes.

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So readable content, especially if it's backed up with data, credible sources, that doesn't just signal credibility to a person reading it, it makes it crystal clear to the AI. So the AI picks up on that clarity as a signal. Absolutely.

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The studies we looked at even show that making content like deeper, but also clearer, can boost its chances of showing up in AI answers by up to 40%. 40%? Wow. That's a huge number.

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Direct link. Okay, so it's not just about the words themselves then, is it? We hear readability and think grammar, sentence structure. Yeah, good point.

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It's definitely more than just the writing. The sources emphasize things like website layout, your on-page SEO elements, you know, the usual suspects there. But also how you strategically use things like video or infographics.

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Right. Think about it. You could have the most brilliant writing, just genius-level stuff.

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But if it's buried in a messy layout or isn't optimized, people will just click away. And now the AI might effectively do the same. And that flags things like bounce rate.

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Exactly. Bounce rates go up, search engines and AI see that as a negative signal. Poor user experience.

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Right. So it's holistic. We need the whole package.

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Okay, so if we want our content easily understood by both humans and AI, where do we start with the writing itself? What's principle number one? Simplicity. That's the word our sources keep hitting. You really have to avoid jargon, those overly complex words.

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But what if the topic is complex? You sometimes need the technical terms. Totally. And that's okay.

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If you have to use a big word, the rule is define it immediately, like right after you use it. And define it in super simple language. Gotcha.

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Like explaining it to someone outside the field. Exactly. Think of it like that.

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You want the information delivered efficiently without forcing the AI or the reader to do heavy lifting just to understand the words. Makes perfect sense. So keep it simple.

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What about structuring sentences and paragraphs? Any like hard rules there? Yeah, this is where it gets really practical and it taps into psychology and processing. Write short sentences. That's a big one.

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How short is short? Well, the general guideline is anything over, say, 20 words starts to feel long. Shorter sentences are just easier to scan, easier to understand, less chance of getting lost. Yes.

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And related to that, keep paragraphs short too. Ah, okay. Like how short? Aim for maybe 100 words or less.

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And crucially, stick to just one main idea per paragraph. One idea. Okay.

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Yeah. This creates white space, breathing room on the page. Yeah.

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Makes it feel less intimidating, you know, especially on a phone screen. Yeah. Walls of text are the worst on mobile.

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Totally. It gives the eyes and the AI these little pauses to digest the info in chunks. I can see that.

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Less cognitive load. Which brings me to active versus passive voice. Classic writing advice.

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Still relevant for AI. Oh, absolutely. Our sources are pretty firm on this one.

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Stick with active voice whenever you can. Why exactly? It just delivers a clearer message. It's more direct.

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The subject does the action. You know, the team analyzed the data. Simple.

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Instead of, the data was analyzed by the team. Right. But passive construction is just wordier, a bit more distant.

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Now passive voice isn't evil. It has its uses, like in formal science papers or if you don't know who did the action. But generally, active voice is more engaging, more dynamic, more like how people actually talk.

(5:52 - 5:59)
And since AI learns from human conversation. Bingo. It prefers that direct, natural style.

(5:59 - 6:07)
Easier to process, easier to extract meaning from. Okay, makes sense. So simple words, short sentences, short paragraphs, active voice.

(6:08 - 6:15)
What about visually structuring the content beyond just the text? Right. The visual and logical flow. Subheadings are your best friend here.

(6:16 - 6:18)
Okay. Use them generously. Seriously.

(6:18 - 6:26)
They make a huge difference. They break up the text, let readers and AI scan quickly, find what they need, digest info in related chunks. Like signposts.

(6:26 - 6:33)
How should we structure them? Like H1, H2, H3. Yeah, exactly. Think of your H1 as the main title, the book title.

(6:33 - 6:39)
H2s are your main sections, like chapters. And H3s are for subsections within those chapters, drilling down a bit. Got it.

(6:39 - 6:47)
Any guideline on how much text should follow a subheading? Good question. Ideally, keep it manageable. Maybe around 250 to 350 words.

(6:47 - 6:56)
You just want to avoid those long, unbroken walls of text that make people's eyes glaze over. Right. And what about lists? Bullet points, numbered lists? Definitely use them.

(6:56 - 7:07)
Our sources really push these. They break things up visually, again, helping readers rest their eyes and pinpoint info fast. And for the AI? They're great for AI, too.

(7:07 - 7:17)
They help the algorithms understand the structure and hierarchy of your information. Makes it much easier for them to pull out key points for summaries or answers. They're like little structured data points within your text.

(7:17 - 7:23)
Okay. Lists and headings. What about actual visuals, images, videos? And you mentioned empty space earlier.

(7:23 - 7:30)
Yeah, visuals are key. Simple images can be really powerful. They can convey an idea quickly, reduce the mental effort needed from the reader.

(7:30 - 7:49)
And things like images, videos, infographics, they cater to different learning styles. Visual auditory learners, wider reach. And how does AI interact with video, for instance? Well, if your videos are optimized, good titles, descriptions, tags with relevant keywords, and importantly, transcripts.

(7:50 - 7:54)
Transcripts. Yes. Transcripts allow the AI to effectively read the video content.

(7:54 - 8:02)
This boosts discoverability, strengthens those EET signals, makes your content richer, more accessible to the AI. Okay. So optimize everything.

(8:02 - 8:08)
Now, about that white space. Sounds like nothing. Why is nothing important? Yeah.

(8:08 - 8:18)
It sounds weird, doesn't it? But white space, or negative space, is just the intentional empty area around things. It doesn't have to be white, just empty. No text.

(8:18 - 8:20)
No images. Okay. And its purpose.

(8:20 - 8:29)
Its purpose is huge. It gives the eye breathing room, stops the page feeling cluttered or overwhelming. It helps the important stuff, your text, your key images really stand out.

(8:29 - 8:36)
It improves focus. Exactly. Improves focus, improves legibility, reduces that cognitive load we talked about.

(8:36 - 8:39)
Yeah. Makes the whole thing look cleaner, more professional. I was thinking examples.

(8:39 - 8:48)
Think about Apple's website, or Google's homepage, or Medium articles. They use white space brilliantly. It guides your attention, conveys simplicity and clarity.

(8:48 - 8:54)
And AI interprets a clean, user-friendly design as a sign of quality. Fascinating. Okay.

(8:54 - 9:07)
So we've got language, sentence structure, page structure, visuals, even empty space. What else contributes to making content appealing to both readers and AI? Credibility. This came up again and again in the sources.

(9:07 - 9:13)
It's absolutely king, meaning you must back up your points. Use data. Use statistics.

(9:14 - 9:16)
Quote experts. And cite your sources. Yes.

(9:16 - 9:19)
Yes. Cite reputable, authoritative sources. Always.

(9:19 - 9:31)
This builds trust with your human audience, obviously, but it also massively reinforces your EEAT standing with generative AI. How so? Well, think about it. AI models can't just invent facts or stats.

(9:31 - 9:33)
Dang it. Reliable sources. Oh.

(9:33 - 9:45)
So content that provides data and shows its work with citations. That's gold for AI. It makes your content much more likely to be trusted, referenced, highlighted in AI answers.

(9:45 - 9:55)
Our sources mentioned a potential boost from citations alone, didn't they? They did, yeah. Something like a 30-40% increase in AI visibility just by adding robust citations. It signals you've done your homework.

(9:55 - 9:56)
Wow. That's huge. Okay.

(9:56 - 10:04)
One more thing that popped out from the sources. Storytelling. How does telling stories fit into optimizing for AI? Seems counterintuitive for logical machines.

(10:04 - 10:14)
It does seem that way, but it's actually a really smart strategy. The sources call it a superpower. Humans are just wired for stories, right? They grab us, help us connect, help us remember, they add emotion.

(10:14 - 10:25)
And while AI seems purely logical, remember what it's trained on. Human conversation. Billions of examples of human conversation, which is packed with stories, anecdotes, experiences.

(10:26 - 10:33)
Ah, okay. So AI recognizes narrative structure. It understands the patterns and the engagement factor.

(10:34 - 10:46)
Stories, even little ones, make content memorable, more engaging, less dry. You can use them in intros to hook people, use case studies to illustrate points, share your own journey. Client transformations, maybe? Perfect example.

(10:46 - 10:56)
Or even talking about failures and what you learn. It makes your voice authentic. It connects with readers on a human level, and that signals high-quality, valuable, human-like content to the AI.

(10:57 - 11:08)
Content worth paying attention to. This has been incredibly useful, so let's bring it all together. For our audience listening, working on their GEO strategies, what's the big takeaway here? I think the main thing is that improving readability.

(11:09 - 11:23)
It's not just about dumbing things down, not at all. It's about being strategic, crafting your content so both humans and these sophisticated AI models can effortlessly understand it, categorize it, prioritize it. So precision, organization, credibility.

(11:24 - 11:29)
Exactly. Communicating with absolute clarity on every level. That resonates across all forms of search, old and new.

(11:30 - 11:49)
It really does feel like future-proofing your content, doesn't it? And as AI gets even more conversational, more discerning, with multimodal search, querying with images, voice, maybe video. It's evolving fast. How might our whole idea of readability change? What could be the next standard for clear, direct content? Definitely something to think about as you optimize.

(11:52 - 12:05)
That wraps up today's episode of Conquer AI Search. Thanks so much for tuning in. If you enjoyed the conversation, make sure to follow or subscribe wherever you're listening, whether that's Spotify, Apple Podcasts, Audible, Amazon Music, or right here on YouTube.

(12:05 - 12:16)
And hey, if you got value out of this episode, consider leaving a rating or review. It really helps us reach more listeners like you. As you continue to refine your content for the AI search landscape, consider this.

(12:16 - 12:31)
How might improving readability not just help AI understand you, but also strengthen your brand's human connection in an increasingly automated world? See you next Saturday with the 7th AI Optimization or Generative Engine Optimization Technique. Thanks for joining us.

(0:05 - 0:16)
Welcome, everyone, to the CONQR AI Search Podcast. This is your guide to really navigating the, well, the whole AI-driven search landscape. We're brought to you by the AI Monitor Team.

(0:16 - 0:19)
I'm Katherine. And I'm Avi. It's great to be back.

(0:23 - 0:36)
Our mission here, it's pretty simple, really. We want to help you boost your visibility in AI searches, and we'll give you simple, actionable steps, things you can actually do without spending a single penny. And well, we can brag just a tiny bit.

(0:37 - 0:42)
We were recently honored by Yes Users. Oh, yeah. Number one consultants for generative engine optimization.

(0:42 - 0:48)
That was after their big survey with hundreds of SaaS companies. That felt good. It really did.

(0:48 - 0:54)
It's, you know, it's proof these strategies work. Absolutely. And this is a really special series for us.

(0:54 - 1:05)
It's part of an 11-episode deep dive. We're detailing the top 11 most effective generative engine optimization techniques. Think of it like your practical roadmap.

(1:05 - 1:10)
Yeah, exactly. And we've already covered some really game-changing stuff in the first four. We have.

(1:10 - 1:24)
First up was implementing that LLMs.txt file, basically, you know, telling AI crawlers how to play nice with your site. Right. The AIrobots.txt. Then we looked at Reddit, how participating there builds authority.

(1:25 - 1:32)
Really important. Yep. Third, we talked about using authoritative citations strategically, getting those mentions in the right places.

(1:32 - 1:46)
Crucial. And just last time we discussed evolving your sort of traditional SEO playbook for this new world of generative engine optimization, or answer engine optimization, as some call it. Okay, so what's next on the list? We're on number five.

(1:46 - 1:55)
Number five. Today we're tackling why public relations PR is absolutely critical now in the age of AI search. Yeah, this one's big.

(1:55 - 1:58)
You might think, oh, PR, that's just press releases. Right. Okay.

(1:58 - 2:07)
But as we're about to see, it's changing massively. And it might just hold the key to your brand's future visibility. It really might.

(2:07 - 2:13)
Okay, let's unpack this one. All right. So the fundamental thing to grasp is how people find information online.

(2:14 - 2:20)
It's just radically changing. Right. Those traditional blue links on Google, they're still there, but they're being displaced more and more.

(2:21 - 2:28)
How so? What's displacing them? Well, a few things. Think about AI-generated summaries first. Like Google's AI overviews.

(2:28 - 2:32)
Yeah, they're everywhere now. Billions of searches per day are showing those now. Billions.

(2:32 - 2:44)
And it's not just Google summaries, is it? What about the chatbots, the conversational interfaces? Exactly. Tools like ChatGT, Claude, they're offering direct answers. You don't even need to click? Pretty much.

(2:44 - 2:57)
You ask a question, you get an answer right there. ChatGT alone, get this, reached like 400 million weekly active users back in February 2025. 400 million weekly.

(2:57 - 3:01)
Wow. That's a huge audience getting info without visiting websites. It's massive.

(3:01 - 3:08)
And then you've also got these standalone AI search platforms popping up. Perplexity AI, Bing Copilot. Right.

(3:08 - 3:14)
More fragmentation, which leads to this zero-click thing I keep hearing about. Yes. Okay, this is where it gets really interesting.

(3:14 - 3:24)
SparkToro did a study recently, found that zero-click searches, they now account for something like 60% of all Google searches. 60%. So most people aren't clicking through.

(3:24 - 3:30)
A huge chunk aren't. Yeah. They get their answer directly from the search results page, the SRP.

(3:30 - 4:03)
They see the AI overview or the featured snippet, get what they need, and boom, done. Okay, so if clicks aren't the main goal, or at least not the only goal, what signals does AI search care about then? What's the new currency? That is the million-dollar question, isn't it? And the answer is, well, it's different. Traditional SEO stuff like backlinks, content relevance, still matters, don't get me wrong, but AI seems to primarily focus on other things, entities like specific brands, people, concepts, and also reputation and authority signals.

(4:04 - 4:09)
But it gathers these signals from all over the web, not just links. So it's a little broader. Much broader.

(4:09 - 4:19)
It fundamentally changes how info gets surfaced, how it gets cited, how it's prioritized. It's less about just a link graph, maybe more like a trust graph, you know? A trust graph. I like that.

(4:19 - 4:31)
And I've seen some, well, some pretty eye-opening research about what correlates with visibility in these AI systems, what's driving that trust. You're probably thinking about the studies on brand mentions. And yeah, they are eye-opening.

(4:31 - 4:55)
Ahrefs looked at 75,000 brands and found that branded web mentions, just mentions of the brand name, had the strongest correlation with visibility in AI overviews. Is it stronger than backlinks? Significantly stronger. Brands with the most web mentions, they showed up in like up to 10 times more AI overviews.

(4:55 - 5:00)
10 times. That really does flip traditional SEO on its head. It absolutely does.

(5:00 - 5:10)
And it wasn't just Ahrefs. Sierra Interactive did a study too, what drives brand mentions in AI answers. Same conclusion, basically.

(5:10 - 5:21)
They found the direct impact of backlinks on brand visibility in LLMs, large language models, was weak or even neutral. Weak or neutral. Wow.

(5:21 - 5:26)
So links aren't the golden ticket anymore. Not in the same way, it seems. Rand Fishkin, you know, founder of Moz.

(5:26 - 5:30)
Sure. He said it back in October 2024. He put it really well.

(5:30 - 5:39)
He said, the currency of Google search was links. The way that you rank in large language models is not that. The currency of large language models is mentions.

(5:40 - 5:51)
Specifically, he said, words that appear frequently near other words across the training data. Training data. What exactly does that encompass? Where is the AI learning from? Good question.

(5:52 - 6:03)
So training data is basically this enormous collection of publicly available text that the LLMs ingest. Like what? Everything. Webpages, blogs, news sites, forums, you name it.

(6:03 - 6:11)
Wikipedia, ebooks, academic papers, even public social media posts. So Twitter, Facebook. If it's public, yeah.

(6:11 - 6:21)
Q&A sites like Reddit and Quora are huge. Product descriptions, reviews, it's vast. So the more often your brand is mentioned in relevant, high quality places within that data.

(6:21 - 6:28)
The more likely the AI is to see it and use it. Exactly. The more likely it is to be included when the AI generates an answer related to what you do.

(6:29 - 6:40)
So, okay, let me see if I've got this straight. Basically, it's as simple as this. If you want your brand to show up consistently in AI tools and LLM responses, just putting good content on your own site, that's not enough anymore.

(6:40 - 6:52)
Not nearly enough. Your brand needs to be talked about accurately, contextually, authoritatively, in the right places, by the right voices, all across the web. Is that the new reality? That's pretty much the core of it, yeah.

(6:52 - 7:06)
It's less about building a static structure of links and more like cultivating an ecosystem, a thriving web of credible mentions around your brand. An ecosystem of mentions. The AI isn't just counting links.

(7:07 - 7:25)
It's looking at the whole picture, the patterns, the context, the frequency of your brand showing up credibly. Which brings us directly to PR. How does digital PR fit into creating this ecosystem? Well, this is exactly why digital PR suddenly becomes not just, you know, nice to have, but absolutely essential.

(7:25 - 7:36)
It's probably one of the most effective ways to secure those authoritative brand mentions. The kind that appear on high-quality, trustworthy sources. The kind of sources AI models are trained on? Precisely.

(7:36 - 7:52)
Those are the sources they learn from and draw from when they build their answers. PR is about getting those high-value mentions. So landing some expert commentary in a major news outlet or maybe contributing to an industry roundup or even just getting covered on a really relevant niche blog.

(7:52 - 8:00)
All of that, yes. Digital PR puts your brand in those important places. It helps build that rich web of brand mentions you talked about.

(8:00 - 8:13)
Exactly. A web that the AI models are likely to crawl, learn from, and then hopefully cite. So it feels like PR's value proposition just got a massive upgrade, right? I think so, yeah.

(8:13 - 8:33)
For years, PR folks have been saying, hey, brand mentions help visibility and authority. Now with AI in the mix, we can say it with way more confidence, that high-quality feature in a top publication, even if it doesn't have a backlink, if it has strong contextual mentions of your brand, that's a huge win now. Maybe even bigger than a link in some cases.

(8:33 - 8:42)
Because those mentions directly teach the LLM about you. Exactly. They help the AI understand who you are, what you do, why you're credible, what topics you're associated with.

(8:42 - 8:53)
And getting surfaced in those AI overviews, which sit right at the top of search results, that's like earned visibility gold. It's earned visibility at massive scale. And think about it.

(8:53 - 9:11)
PR's core job is to position your brand as a credible expert, right? A go-to solution. So when an AI tool actually selects your brand to help answer a user's query, that's an incredibly powerful signal. It reinforces the very authority and trustworthiness that PR aims to build.

(9:11 - 9:21)
OK, that makes perfect sense. But it can't all be positive, can it? What are the potential downsides of relying on LLM visibility? You're right. It's definitely a double-edged sword.

(9:22 - 9:25)
Let's talk upsides first, though. OK. The big one is massive reach.

(9:25 - 9:29)
Your brand gets seen by tons of users interacting with these AI summaries. Right. Exposure.

(9:30 - 9:39)
Then there's perceived authority. Being mentioned by an AI, it carries this sort of implicit endorsement. Users tend to assume the AI is surfacing reliable stuff.

(9:39 - 9:45)
Sure. Consistent exposure builds brand awareness, top-of-mind recall, even if they don't click right then. OK.

(9:45 - 9:51)
But the downside. It seems like the big one is clicks, right? The thing traditional SEO always measured. That's the major challenge.

(9:51 - 9:58)
Yeah. If the AI answers the question well enough right there in the overview... Why would they click through to your site? Exactly. They might not need to.

(9:58 - 10:10)
Which leads straight to attribution challenges. How so? Well, these AI responses often blend info from multiple sources. And they don't always cite them clearly or consistently.

(10:10 - 10:20)
So it becomes really hard to track when your brand was mentioned or measure the direct impact, like a click or a conversion from that mention. And you mentioned inconsistency. Yeah.

(10:20 - 10:29)
AI responses can vary depending on the specific model, how the user phrases the query, even the time of day sometimes. So your visibility might fluctuate. OK.

(10:29 - 10:42)
So less direct traffic, hard to track. What does the data show? Well, we're seeing it already. Since AI overviews really rolled out, a lot of search marketers are reporting that impressions in Search Console are kind of creeping up.

(10:42 - 10:44)
OK. So people are seeing the results. Clicks are flat.

(10:44 - 10:56)
Or even falling. It's a pretty clear sign users are getting info directly from the AI, which, you know, if you're only measuring clicks, that's frustrating. Your old KPIs, key performance indicators, might look bad.

(10:57 - 11:07)
It really does feel like we're stepping back in time a bit, doesn't it? To like old school PR before everything was digitally trackable. It kind of does. You get that great magazine feature.

(11:07 - 11:17)
You knew it was valuable, but you couldn't track exactly who read it or what they did next. Precisely. And now we're sort of back there, but in this new AI context.

(11:17 - 11:25)
We don't always have reliable ways to measure every AI mentions direct impact. But the impact is still happening. We believe so, yes.

(11:25 - 11:32)
Which means our attribution models, the ones relying purely on direct clicks, they're becoming outdated fast. Yeah. So we need to shift focus.

(11:33 - 11:47)
Definitely. We need to measure things like brand awareness, sentiment, recall more broadly, understand that indirect impact. Like someone sees your brand in an AI answer, doesn't click them, but maybe they search for you later or convert through a different channel.

(11:47 - 12:00)
Exactly that. That indirect path is becoming much more significant. So what should brands be tracking then? What are the new metrics? Well, smart brands are looking at a basket of things, growth in search volume for their brand name and key product terms.

(12:00 - 12:07)
Okay. Makes sense. They're looking for uplift in direct website traffic, especially after big PR pushes or coverage.

(12:07 - 12:18)
Correlating activity. Yeah. And using social listening tools, brand sentiment analysis, looking for spikes in visibility or positive mentions that might line up with AI features.

(12:19 - 12:27)
So it's about reading between the lines a bit more. Pretty much. Understanding that influence and visibility don't always come with a neat little tracking link attached.

(12:27 - 12:34)
LLM visibility. It's often about long-term brand building, reputation, not just those immediate clicks. Okay.

(12:34 - 12:42)
So given this whole new landscape, it sounds like, well, SEO teams and PR teams really need to talk to each other now. Oh, absolutely. They can't operate in silos anymore.

(12:43 - 12:48)
They have to align on target topics, audiences, messaging. It's crucial. So collaboration is step one.

(12:49 - 13:03)
What else? What are the practical steps for brands wanting to leverage PR for AI visibility? Strategically, you need to prioritize getting high-quality mentions from authoritative sources. Media outlets, key influencers in your space. Quality over quantity.

(13:03 - 13:12)
Definitely. And build strong topical authority. Consistently get coverage around the core subjects you want your brand to own in AI results.

(13:12 - 13:20)
That consistency helps the AI make the connection. What about the actual content of the PR? Does that need to change? Yeah. Think about being quotable.

(13:20 - 13:30)
Craft unique insights, maybe some original data points, provocative quotes. Stuff that journalists and bloggers actually want to pick up and cite. Make it easy for them to mention you.

(13:30 - 13:36)
Exactly. Right. So we've laid out how PR can really boost visibility in AI search.

(13:36 - 13:48)
But it's not just about using AI, is it? AI itself is changing the PR game, sometimes in challenging ways. Oh, absolutely. There's definitely another side to the rise of generative AI.

(13:48 - 13:59)
While amazing for drafting things quickly, it doesn't replace human creativity, right? And we're seeing this flood of content that's, well, kind of similar. Lifeless, even. AI-generated content can be pretty bland.

(14:00 - 14:09)
It can be. And if it's not edited well by a human, it can feel generic, maybe even erode trust because people start questioning if it's authentic or accurate. It's a quality control issue.

(14:09 - 14:25)
And it causes confusion, too, right? I heard about an experiment where people couldn't reliably tell original human writing from AI text. Yeah, that highlights the practical confusion. And we're seeing clients now starting to ask for proof that AI wasn't used or wasn't the primary author in PR work.

(14:25 - 14:36)
Really? Demanding proof? And PR pros themselves. They need to be careful. They have to verify the originality of materials they get from clients before bitching them to protect their own relationships with the media.

(14:36 - 14:42)
So transparency and verification are becoming huge. Huge. Which leads to the ethical side.

(14:42 - 15:03)
With generative AI being so pervasive, it's really crucial that PR agencies, individual pros, everyone, develops a clear ethics code around AI use. What would that involve? Things like being transparent about AI's role, respecting privacy, ensuring data used to train or prompt AI is handled responsibly. It's about maintaining trust, basically.

(15:04 - 15:13)
That's the bottom line, like that quote you mentioned earlier. In the end, ethical AI use is about maintaining trust because once that's gone, no tool can bring it back. That really sums it up.

(15:13 - 15:19)
Use AI to enhance the connection. Don't let it undermine the trust that connection relies on. Couldn't have said it better.

(15:21 - 15:37)
So yeah, we've seen PR is definitely taking a starring role now in the AI search era. From shaping the AI's training data with quality mentions to building that deep reputation that goes beyond just links. PR isn't just supporting anymore.

(15:37 - 15:49)
It's kind of leading the charge for visibility. Okay, so here's a final thought to leave everyone with. We know AI systems are, as you said, hungry for high-quality, context-rich signals from human content.

(15:49 - 16:06)
Right. And we know PR is vital for creating and placing that high-quality content. So what's our collective responsibility here? What's our responsibility in making sure the information AI learns from the information PR helps generate and disseminate is actually true? That it has integrity? That's a big question.

(16:06 - 16:16)
It feels like it goes beyond just marketing or visibility. It's about the future of information and communication itself, isn't it? Something for all of us, especially brands, to really think about. Definitely something to mull over.

(16:22 - 16:38)
And that's a wrap on today's episode of the Conquer AI Search with AI podcast. We just dove deep into why PR is a game changer in the age of AI search and how you can master it like a pro. But hey, this conversation doesn't stop here.

(16:38 - 16:54)
If you've got thoughts, questions, or something to add that we missed, drop a comment below. Your take could spark the next big discussion and help fellow listeners, and yeah, us too, level up. Ready to take action? Head over to AI Monitor's website.

(16:55 - 17:15)
We've got tools and geo-specific services to help B2B SaaS companies like yours boost AI visibility and get discovered where it counts. Loved this episode? Hit that follow or subscribe button on Spotify, Apple Podcasts, YouTube, or wherever you're listening. And if we brought you value, leave us a rating or review.

(17:15 - 17:27)
It seriously helps us reach more awesome people like you. Join us next Saturday, where we'll break down the sixth generative engine optimization technique to keep you ahead of the curve. Stay sharp.

(17:28 - 17:35)
We're here to help you dominate AI search. Until then, keep innovating, and we'll catch you in the next one.

(Transcribed by TurboScribe.ai. Go Unlimited to remove this message.)

(0:05 - 0:14)
Welcome to the Conquer AI Search podcast. We're your AI monitor team source for figuring out this constantly changing world of digital visibility. I'm Catherine.

(0:14 - 0:34)
And I'm Avi. Great to be back. So we are well into our 11 part series now, looking at the most effective generative engine optimization techniques, you know, Geo, we've already covered implementing LLMs.txt files, the maybe surprising impact of Reddit and using authoritative citations strategically.

(0:37 - 0:53)
And today we're taking all that and sort of zooming out a bit. We're looking at how to evolve your entire traditional SEO playbook, your best practices for this new world of generative engine optimization or answer engine optimization, AEO, as some folks call it. Yeah, exactly.

(0:53 - 1:03)
And it's not about throwing out everything you learned about SEO, not at all. It's more about adapting it, building on it for AI. Okay, but here's something that jumped out immediately, something maybe a bit counterintuitive.

(1:04 - 1:27)
We found that the standard advice on keyword density, you know, the 1% to 2.5% range, every SEO consultant mentions, well, that might actually have zero impact now or get this, it could even hurt your Geo performance. Can you tell us more about what the AI monitor team found there? Yeah, this is really quite crucial. We ran hundreds of tests, literally hundreds of trials and errors here at AI monitor.

(1:27 - 1:40)
And what we consistently found is that right now, as of today, June 20th, 2025, a keyword density of 0.8% seems to hit the sweet spot. 0.8%? Yeah. That specific? That specific.

(1:40 - 1:52)
It yields the best combined results for both traditional SEO and your Geo efforts. It's data backed from all that testing. It really shifts how you should think about optimizing your content.

(1:52 - 1:55)
Wow. Okay. That 0.8% figure is gold dust for our listeners.

(1:56 - 2:04)
So keeping that very specific number in mind, let's talk bigger picture. People often say SEO is dead, but you're saying that's not quite it. Not really, no.

(2:04 - 2:13)
It's more accurate to say SEO isn't being replaced, it's expanding. It's evolving into this bigger thing, Geo. Your traditional SEO skills, they're still absolutely vital.

(2:13 - 2:25)
They're the foundation, the baseline. So what's the key difference then, SEO versus Geo? Well, think about it like this. Traditional SEO is mostly about getting ranked in that list of blue links on Google, right? You want to be high up on that page.

(2:26 - 2:39)
Geo though, is optimizing for the AI to generate a comprehensive direct answer. Like in Google's AI overviews, or when you ask ChatGPT or Gemini a question. The goal is to be part of that synthesized answer, not just a link below it.

(2:39 - 2:52)
And that shift has real consequences, doesn't it? We're seeing things like Google AI overviews, grab clicks that used to go to websites. Some reports show users getting their answers directly from the AI overview and never clicking through. Absolutely.

(2:53 - 2:58)
Click-through rates from traditional results can definitely take a hit. Yeah. But it's not always a simple replacement.

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We're seeing this interesting reverse causality, you could call it. Reverse causality, what do you mean? Well, someone might first encounter your brand or product in an AI-generated answer. Maybe it's mentioned in a list or as a recommendation.

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Then they might go to Google search to specifically look you up, you know, to check reviews or pricing. Ah, so AI introduces and then Google validates a new kind of customer journey. Exactly.

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It's a different funnel, starting with AI discovery. Okay, that makes a lot of sense. So if people are following along, the next big question is probably keywords.

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How does our keyword strategy need to change right now for AI? Right. The old way of just chasing high volume head terms, those short, broad keywords, it's just not cutting it anymore. AI tools, they seem to really like long tail keywords, conversational phrases, questions.

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Like how people actually talk. Pretty much. Think about Google's own data, they say 15% of all searches are queries they've never seen before.

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That tells you there's a massive appetite for niche-specific content. So what are the concrete steps? How do we adapt? Okay, first, go low. Don't automatically filter out keywords just because their monthly search volume looks low.

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You need to map out more terms, including those lower volume, more specific ones. More niche terms. Exactly.

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Second, be conversational. Tap into the actual questions people are asking. Look at Google's People Also Ask boxes.

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Use tools like Answer the Public. Check out forums, like Reddit, which we've talked about before. Right.

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Tying back to that previous deep dive. And it's not just the exact phrase they type, is it? Semantic search comes into play. Absolutely.

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You need to use variations. Optimize for semantic search. The underlying meaning.

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The intent behind the words. Use related phrases. Synonyms.

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A really effective tactic here is creating helpful FAQ sections right within your content. Like an FAQ page. Or within blog posts.

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Within the content itself often works best. It lets you target multiple long-tail questions naturally. We saw Kiehl's, for example, get something like over 550 AI overview rankings.

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Partly because they structure their content well with FAQs. That's impressive. And again, remember that keyword density point we made.

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That .8%. That's a direct, actionable change to your keyword strategy, moving away from that old 1-2.5% advice. Got it. Precision matters.

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Okay. Moving on. Content clarity and structure.

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This sounds fundamental for AI readability. How do we tackle this? Yeah, it's critical. AI models are built to pull out concise, structured information.

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So your content needs to be, well, easy for them to digest. That means clear, descriptive headings. H1, H2, H3 is outlining the structure.

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Striking things down. Exactly. Break up big walls of text, use short paragraphs, bullet points, numbered lists.

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Make it snackable. It's also really good practice to put key takeaways right near the top. Like a summary up front.

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Sort of, yeah. Helps both users and AI grasp the main points quickly. And in terms of writing style.

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Yes. Lean into natural language. Right? Like you're answering a question someone actually asked.

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Use common question formats. Avoid super technical jargon unless your audience absolutely expects it. And featured snippets.

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Still relevant. Very much so. AI often pulls from featured snippet content.

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So optimizing for those with concise definitions and bullet points helps. Oh, and don't forget tables. Tables.

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Really? Yeah. AI can parse structured data in tables really well. Especially if they have clear, descriptive headers.

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It makes complex information much more accessible for the AI. Interesting. So clear structure, snackable content, natural language, maybe some tables.

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But none of that matters if the AI can't even find or access the page, right? Let's talk technical SEO. Is it still the bedrock? Absolutely. Maybe even more so now.

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Technical SEO determines if your content is even visible and interpretable by AI crawlers. Without a solid technical foundation, you're invisible. Okay.

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What are the non-negotiables? Well, HTTPS. Secure connection. It's a ranking factor.

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Plus, essential for trust and privacy. That's table stakes. Then mobile optimization.

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Huge. Google uses mobile-first indexing. Most searches are mobile.

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And AI often previews mobile layouts, you said. Right. So a bad mobile experience is a bad signal to AI.

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Then you've got to be fixing crawl errors. These block search engines and AI bots check for them regularly, like monthly audits. Keeps the pathways clear.

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Exactly. And site speed. Super important.

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AI prioritizes fast sites. Remember something like 53% of mobile users bounce if a page takes more than three seconds to load. Speed matters.

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What about site structure itself? That falls under crawlability and indexation. A logical site architecture, good internal linking, it helps search engines and large language models, the LLMs, navigate your site efficiently. Okay, now, schema markup.

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This keeps coming up as increasingly important for AI. Tell us about that. Schema is massive.

(7:48 - 8:04)
Yeah. It's like adding little labels to your content that explicitly tell search engines and AI what the content is about. Is it for product? An FAQ? A how-to guide? An article? A review? Video? Local business info? So, it removes ambiguity for the AI.

(8:04 - 8:12)
Precisely. It helps AI surface accurate info and really boost your chances for rich snippets and appearing correctly in AI answers. And one more technical point, JavaScript.

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Oh, yes. The bane of some crawlers. Still can be.

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Many AI crawlers, including GPTBot from OpenAI and CloudBot from Anthropic, don't execute JavaScript effectively or at all. So, critical content needs to be in the raw HTML, server-rendered if possible, not hidden behind client-side JavaScript execution. Good tip.

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Okay, technical foundations sorted. How do we then build that trust and authority? We talk about Google's E-E-A-T signals, experience, expertise, authoritativeness, trustworthiness. How does that apply to AI? AI models are explicitly trained to prioritize credible, authoritative information.

(8:46 - 8:52)
So demonstrating E-E-T is key. Practically, that means showcasing author expertise, detailed bios, credentials. Show your work, basically.

(8:52 - 9:02)
Yeah. Site-reputable sources, link out to original studies, keep those references up to date. High-quality backlinks from trusted sites still matter a lot for authority.

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And what about the human edge? AI can generate text, but what can humans provide that AI can't replicate easily? That's where the experience part of E-E-T really shines. AI struggles with genuine lived experience, original thinking, deep product expertise based on actual use. So include unique frameworks, specific use case details only an expert would know, bring in distinct voices and points of view.

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Make it unique? Yes, and present balance views. AI aims for neutrality, so showing pros and cons, strengths and weaknesses that resonates. Also, proprietary data, your own surveys, case studies that makes your content inherently unique and valuable to AI.

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Right. Now, something often seen as separate, but you're saying it impacts GEO, user experience, UX. How does a good UX help with AI visibility? Because a bad UX sends bad signals.

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A slow, confusing site frustrates users, increases bounce rates, lowers dwell time. And Google and AI interpret these as signs that the content isn't high quality or helpful. So dwell time matters.

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How long people stay on the page? It seems to be a significant engagement signal, yes. Keep users engaged with visuals, clear calls to action, good internal linking, and accessibility. Don't forget website accessibility, AI considers this too.

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What about things like images and videos? High quality multimedia is great for UX, but make sure you include descriptive alt text for images and transcripts for videos. This helps users and helps AI understand the content of that media. Okay, and keeping things current, content freshness.

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Oh, absolutely essential. AI-driven search relies heavily on timeliness for accuracy, outdated information gets penalized. Keep content fresh.

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Use a content calendar, plan regular updates for stats, strategies, especially for fast moving topics. Makes sense. Now, this is fascinating.

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Where does AI actually get its information? It's not just our websites, is it? Not at all. AI pulls from a really diverse range of sources. Yes, your site, but also independent blogs, niche affiliate sites, industry publications.

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We've seen before that while top tier sources are good, AI often cites mid-tier sources too. So you don't have to be the New York Times to get cited. Definitely not.

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And the preferences vary. ChatGPT, interestingly, seems to cite lower ranking Google results positioned 21, plus almost 90% of the time. Often content focused on very specific use cases.

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And for Google's AI overviews. Quora comes up top, followed by Reddit. Again, highlighting those community and Q&A platforms we discussed earlier.

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But you also mentioned our own research showing business sites get cited too. Yeah, about 50% of ChatGPT links point to business service sites. So there's definitely potential for direct citation if your content is well-optimized, LM-friendly.

(11:41 - 11:48)
And there are even direct submission programs emerging. Right. Things like Perplexity's Merchant Program, OpenAI's Search Product Discovery Initiative.

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Brands can submit product catalogs directly for AI recommendations. It's a very direct route. This is all changing so fast.

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Which brings us to measurement. How do we track success in this new GEO world? Traditional analytics don't quite cut it, do they? Not directly for AI-driven traffic, no. So we need new approaches.

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First, monitor your referral traffic. Look for hits coming from domains like chat.openai.com, perplexity.ai, claude.ai, and so on. Check the referrers.

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What else? Watch your branded search volume. If you see more people searching Google specifically for your brand name, maybe adding reviews or pricing, that could be an indirect sign they discovered you via AI first. That inverse customer journey again.

(12:30 - 12:40)
Makes sense. How do we check if our content is actually showing up? You have to actively test. Regularly put relevant prompts into chat.gpt, gemini, claude, perplexity.

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See if your brand, your content, appears in AI overviews or GenAI results. Are you in lists? Cited as a source. Take screenshots.

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Track it. So manual checking is still part of it? For now, yes. But tools are catching up.

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SEO platforms like RFs and SEMrush are starting to integrate tracking for AI overview appearances. We're seeing new metrics emerge. Like what? Things like an AI visibility score tracking how often you appear, how prominently, sentiment, also citation frequency, share of voice specifically within AI results, and sentiment analysis of how your brand is mentioned in AI outputs.

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These give you a much clearer picture of your GEO performance. Okay, so wrapping this all up. The big message for everyone listening seems to be SEO isn't dead, but it's definitely transforming.

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Well, that about wraps up today's Conquer AI search session. Quite a journey into how SEO is evolving. And remember the big takeaway on keywords.

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For top performance across both old and new search, our AI Monitor team's latest findings as of June 20, 2025, suggest aiming for that 0.8% density. Yeah, that's the number for now. And hey, if you found this useful, please do follow or subscribe wherever you listen.

(13:54 - 14:04)
Spotify, Apple Podcasts, Audible, Amazon Music, maybe right here on YouTube. And if you got value out of this, maybe consider leaving us a rating or a review. It genuinely helps us reach more people like you.

(14:04 - 14:10)
We'd really appreciate it. Absolutely. We'll see you next Saturday to talk about the fifth generative engine optimization technique.

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And just a thought to leave you with. In this AI-first world, your website isn't just content for people anymore. It's data for machines too.

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The better you structure that data, the better you can shape how AI understands your brand.