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Complete AI SEO Course for Beginners: Learn AEO in 86 Minutes — Transcript

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0:00Hey everyone, my name is Samo and welcome to the answer engine optimization or AEO course by HRS.
0:06In this course, I'll be teaching you how to get traffic from AI search and to get more brand
0:10visibility in it. This course will have a heavy focus on execution. And while the topic might
0:15be new to many of you, I don't want you to feel intimidated, especially if you have a background
0:20in SEO because SEO is the foundation of AEO. Now, here's why you need to pay attention to this right
0:28now. As of December 2025, the presence of an AI overview on Google reduces the click-through rate
0:33for the number one ranking page by 58%. That means for every 100 clicks you used to get, Google now
0:40keeps 58 of them. Chat GPT alone has 900 million weekly users. It handles roughly 12% of Google
0:47search volume. And AI traffic to websites has grown 9.7 times in the past year. So, you can
0:53either ignore the shift and watch your traffic shrink while raising your fist at the clouds,
0:58or you can learn how it works and capitalize on it. Because here's the thing most people miss.
1:03In June 2025, AI search accounted for just 0.5% of our traffic, but it drove 12.1% of our signups.
1:12That's a 23 times higher conversion rate than organic search. Search has changed and it's no
1:17longer just about clicks because AI traffic is one of the highest converting channels we've
1:23ever seen. So, let's start with the basics. In this first lesson, I'm going to explain what
1:27AEO actually is, why it matters, and give you a road map for the entire course so you know
1:33exactly what's coming. So, what is answer engine optimization? AEO or answer engine optimization
1:40is the practice of making your content visible and useful to AI systems that deliver direct answers.
1:46That's Google AI overviews, ChatGBT, Perplexity, Gemini, Copilot, basically any platform where
1:53AI is generating a response and choosing who to site. You'll also hear this called GEO, generative
1:59engine optimization, or LLMO, large language model optimization. They all mean essentially the same
2:05thing. So, we'll use AEO throughout this course. Now, you might be wondering, how is this different
2:10from traditional SEO? Well, in traditional SEO, you optimize web pages to rank higher
2:16in a list of search results. You're competing for positions. The user sees your blue link,
2:21clicks it, and lands on your site. In AEO, there is no list. The AI reads from dozens of sources,
2:28synthesizes an answer, and decides who to mention or site. You're not competing for a position,
2:34you're competing for a mention. And the rules for getting mentioned are a bit different
2:38from the rules for ranking in organic blue link results. Now, we'll break down exactly how that
2:43works in module one. But for now, the key thing to understand is this. AEO doesn't replace SEO.
2:50It builds on top of it. Think of SEO as your foundation and AEO as futureproofing your
2:55online presence. The fundamentals still matter. quality content, authority, technical health,
3:01but the strategy needs to evolve because the way people find information is changing.
3:06Now, I know some of you might be thinking, "Is AI just going to kill SEO completely?" And I get it,
3:13but this is not the end of SEO. Ethan Smith from Graphite talked about the zero sum bias on HR's
3:18podcast, and this is a cognitive bias based on the assumption that if something new goes up,
3:24something old must go down. And we saw the exact same thing in 2010 when the app store blew up.
3:31Everyone said, "The web is going away. Mobile apps are taking over. Only old people use websites."
3:37And yes, mobile apps did blow up. That promise was real. But the web didn't die. It grew
3:43alongside these apps. AI search is likely going to be the same story. It is growing fast. Those
3:49numbers I just showed you are real. But Google still processes billions of searches per day.
3:55Traditional organic traffic still drives massive business value. So, the smart move isn't to panic,
4:02it's to play both games. And let me be real with you, most businesses haven't even started
4:08thinking about this. We looked at HF's own data and found that our content and product pages have
4:13been mentioned 7,470 times across 2,39 pages in AI search without any effort to optimize for it.
4:23That's all happening organically because we've been doing solid SEO and creating content that
4:28people find useful. Now, imagine what happens when you actually start intentionally optimizing for
4:34this. When you know which platforms site what, when you understand how AI decides
4:40who to recommend when you're actively building the signals that make AI want to mention your brand.
4:46That's exactly what this course will teach you. The course is broken down into four modules plus
4:51this introduction. Module one is about how AI search actually works. We'll cover the mechanics,
4:57how AI finds content, how it decides what to site, how different platforms like Chat GBT, Google AI
5:03overviews, and Perplexity actually differ from each other, and what AI visibility actually looks
5:09like for different types of businesses. This is the foundation that makes everything else make
5:14sense. Module two is all about strategy. I'll show you the data behind why brand mentions are the
5:19single strongest lever for AI visibility, stronger than backlinks, domain rating, or anything else.
5:26You'll learn keyword research for AEO, prompt research, and how to figure out where your brand
5:31stands versus competitors. Module three is about execution. This is where the actual work happens.
5:38How to create content that gets cited, how to earn mentions and citations for other sites, YouTube
5:43optimization for AI visibility, which no other course covers, and the technical stuff to make
5:49sure AI can actually find and crawl your content. In module four is about measurement. You'll learn
5:55how to set up your analytics for AI traffic, how to run competitive audits to find your brand gaps,
6:00and how to evaluate whether AEO is actually worth the investment for your business. By the end of
6:06the course, you should be able to put together a concrete action plan that's bespoke for your
6:11business with workflows to actually do this stuff immediately. All right, so that's the lay of the
6:17land. In the next lesson, we're diving straight into how AI search engines actually find and site
6:23content, including the concept of query fan out, which is probably the single most important thing
6:28to understand about why AI search works the way that it does. I'll see you in the next lesson.
6:34Hey, it's Samo and welcome to the first module which is on how AI search actually works. In this
6:39lesson, I'm going to walk you through the three things you need to understand about how AI search
6:44engines find, evaluate, and site content. Because here's the thing, if you don't understand how AI
6:50search works under the hood, every optimization tip you hear is just going to feel like a random
6:57list of tactics. And I don't want that for you. I want you to understand the why behind
7:02every strategy we cover in this course. Let's get started. So where does AI actually get its
7:08information? This is probably the most important distinction to understand. AI search engines have
7:13two sources of information and they work very differently. The first is training data. This
7:18is the massive collection of text that the AI was originally trained on. So books, websites, PDFs,
7:25social media, YouTube transcripts, basically a snapshot of the internet. So when you ask ChatGpt,
7:32"Who is the CEO of Apple?" and it instantly says Tim Cook without searching anything,
7:38that's coming from training data. It already learned that pattern. But here's the problem
7:42with training data. It's static. It gets updated maybe every 6 months or so. So if you launched
7:48your product last week, the AI doesn't know about it yet. not from training data at least.
7:54And that's where the second source comes in, real time retrieval. This is where rag or retrieval
7:58augmented generation comes into play. It sounds complicated, but Patrick Stock said it best.
8:04Uh then you've got the the retrieved pages, which is like a secondary process. So you've got the
8:09the trained LLM data and then you've got the data where it goes out and fetches a bunch of relevant
8:14pages and those come with other probabilities. For example, when ChatGpt or Google's AI mode
8:20needs fresh information, or when the question is too specific for training data alone,
8:25it goes out, it searches the web using APIs, it pulls back a bunch of pages, reads through them,
8:31and then generates a response based on what it found. Now, why does this matter for you?
8:36Because it means there are two ways to influence what AI says about your brand. The first is to be
8:42mentioned so widely across the web that you're baked into the training data itself. And second
8:48is to make sure your content shows up when the AI searches the web in real time. And guess what?
8:54We already know how to do that. That's SEO. The skills you already have from traditional SEO,
9:00ranking in Google, earning backlinks, creating quality content, those directly influence
9:05whether AI picks up your pages during real-time retrieval. Now, here's where it gets interesting.
9:10The AI doesn't just search for the exact thing you typed in. Let me explain. Search engines used to
9:15work one to one. One query, one set of results. Then they evolved to many to one where different
9:21queries like Sydney plumber and plumbing service in Sydney could return the same results. But AI
9:28search has flipped the model to one to many. One search gets expanded into many. And this technique
9:36is called query fo. For example, when someone enters a prompt like, "Plan me a 5-day trip to
9:41Japan in November." The AI fans it out into dozens of smaller longtail subqueries. Things like, "Best
9:48neighborhoods to stay in Tokyo, November weather in Kyoto, Japan Rail Pass worth it?" All running
9:53simultaneously behind the scenes. It then pulls information from multiple sources across the web
10:00and combines it into one complete answer. In fact, research from Seir Interactive in Nective
10:05found that the average prompt triggers 9 to 11 fan out queries with some going as high as 28.
10:13And ChatGpt's deep research mode ran 420 searches for a single query about buying a red phone case.
10:21So, if your content ranks for those niche specific queries, your brand has a much better chance
10:26of being included in the AI's final response. And this is a huge shift from traditional SEO
10:32where you could optimize one page for one target keyword and call it a day. In AI search, you need
10:39to be relevant across an entire topic. And I could even argue across an entire niche. Because if your
10:46page about how to start a podcast only covers the basics, but doesn't mention equipment, hosting, or
10:53promotion, the AI is going to find someone else's page that does. Now you might be wondering, can I
11:00see these fanout queries? You sure can. In the AI responses report in HFS brand radar, you can see
11:06the fan out queries for chat GPT and perplexity prompts. But there's an important caveat. Despina
11:12from HFS wrote in her guide on query fan out that these aren't like traditional longtail queries.
11:18They're synthetic, generated by AI in the moment. They're inconsistent. The same prompt can trigger
11:24different fanouts every time. And over 95% of them have zero search volume because real humans
11:32would never type them. So don't think of fano queries as a new keyword list to optimize for.
11:38Think of them as a window into what topics the AI considers important for a given question.
11:44We'll get into exactly how to use this strategically in module 2 because for now
11:49we need to talk about how AI decides who to actually site. In traditional search rankings
11:54are relatively stable. Like if you're number three for a keyword today, you're probably going to be
11:59somewhere around there tomorrow. But AI citations are probabilistic. Patrick Stocks explained this
12:04really well. He said, "AI outputs are built on probabilities on top of probabilities on top of
12:10probabilities. The training data creates patterns. The retrieve pages add their own signals and then
12:16there's a temperature setting that introduces randomness so the AI doesn't generate the exact
12:22same answer every time." Now, what that means in practice is that if you ask the same question five
12:28times, you might get cited three out of five. Or the AI might mention your competitor twice and
12:34you twice and someone else once. There's no fixed position to rank for. This is why we talk about AI
12:40visibility rather than AI rankings. It's more like a probability distribution than a leaderboard.
12:46Now, that said, there are patterns in what gets cited more often. Based on the data we've studied
12:51at HRES, consensus matters. If multiple sources on the web say the same thing about your brand, AI is
12:58more likely to repeat it. And the more places your brand is mentioned in a consistent way, the higher
13:04the probability the AI picks it up. Freshness matters. AI cited content tends to be about 25%
13:10fresher than what you'd see in a traditional SER. The AI is actively looking for recent information,
13:16especially for topics that change. Authority still matters. Pages that rank well in traditional
13:22search have a major head start. Our data shows that 76% of AI overview citations come from pages
13:29already in the top 10 of Google. So, I'll hit that gong one more time. SEO is the foundation of AEO,
13:37but it's not only about Google rankings. 14% of pages cited in AI overviews don't rank in Google's
13:44top 100 at all. And for platforms like Chad GBT, the overlap with Google's results is even lower.
13:51So there's real opportunity for brands that aren't dominant in traditional search to still show up
13:56in AI. So let's tie all of this together. AI search engines pull from training data
14:01and real time web search. They expand your one query into dozens of subqueries through fan out.
14:08They merge and score results from all of those searches. and then they generate a
14:12response that's probabilistic, not fixed, based on patterns, consensus, freshness, and authority.
14:19Understanding this process is what makes every other lesson in this course make sense. So when I
14:25tell you to earn more brand mentions, it's because of how consensus drives probability. When I talk
14:31about topic coverage, it's because of query fan out. When I say that SEO is the foundation again,
14:37it's because 76% of citations come from pages already ranking well. Now that you understand the
14:43mechanics, the obvious next question is, do all AI platforms work the same way? And the answer is
14:52not even close. Not even close. In the next lesson, we're going to compare AI overviews,
14:57chatbt, Perplexity, and Google's AI mode side by side. And the data on how different they
15:03are is pretty surprising. I'll see you in the next lesson. Hey, it's Samo and welcome to the
15:08second lesson which is on the differences between AI search platforms. Now, in the last lesson,
15:14I covered how AI search engines find and site content. But here's what I didn't tell you.
15:19They don't all do it the same way. And this matters a lot more than most people realize.
15:25Because if you're treating AI search as one thing and optimizing for it the same way across
15:30the board, you're likely leaving visibility on the table. So in this lesson, I'm going to break
15:35down the major AI search platforms like Google's [clears throat] AI overviews, Google's AI mode,
15:40ChatGpt, and Perplexity, and show you the data on just how different optimization for these
15:46platforms are. Let me start with a stat that might surprise you. We looked at the top 50
15:50most cited domains across Google AI overviews, ChatgBT, and Perplexity. And out of those 50,
15:57only seven appeared on all three platforms. That's only a 14% overlap. Think about that for a second.
16:04If you're only optimizing for one platform, you're potentially invisible on the others.
16:09And it gets even more interesting when you look at what each platform actually prefers. Google AI
16:15overviews favor authoritative established sites. Think health, finance, encyclopedic content,
16:20and Google owned properties like YouTube. In fact, YouTube accounts for about 5.6% of all AI overview
16:28citations. And just look at how fast they're adding YouTube videos to their AI overviews.
16:33And obviously, Reddit's big here, too. ChatGpt leans heavily toward publishers and media.
16:38For example, authoritative sites like Reddit, Wikipedia, Amazon, Forbes, Business Insider,
16:44and Wired are some of the most cited domains here. In fact, the median domain rating of
16:49Chat GBPT's top-sighted pages is 90. So, it's pulling from high authority publishers, and
16:56that's partly because of licensing deals OpenAI has with some of these outlets. Perplexity is
17:02actually the most aligned with traditional Google search. About 28.6% 6% of perplexity citations
17:08come from pages that rank in Google's top 10. Compare that to Chat GBT, which only overlaps
17:13with Google's top 10 about 8 to 10% of the time. So, if you're already ranking well in Google,
17:19Perplexity is probably where you'll see the most immediate AI visibility. And then there's Google's
17:24AI mode. Now, you might assume that since AI mode and AI overviews are both Google products,
17:30they'd site similar sources. Well, they don't. The citation overlap between AI overviews and
17:36AI mode is only 13.7%. Despite the fact that their answers are 86% semantically similar,
17:44meaning they're saying similar things but pulling from completely different sources.
17:49AI mode's top-sighted domain is YouTube by a wide margin, followed by Google and Wikipedia.
17:56We also found that it cites Quora 3.5 times more than AI overviews and pulls from social platforms
18:02like Facebook and Instagram much more heavily. So the takeaway here is clear. AI search is not one
18:09thing. Each platform has its own index, its own biases, and its own preferences for what kind of
18:15sources it likes to site. So which platform should you focus on? This is the practical question and I
18:22think it's important to be strategic here rather than trying to optimize for everything at once.
18:27There are really two things to consider. The first is market share. As of right now,
18:31Google's AI features and chat GBT account for the vast majority of AI search traffic.
18:37Proplexity is growing, but it's still a fraction of the volume. So, if you have to prioritize,
18:42Google and chat GBT are where most of the eyeballs are, at least for now. The second thing to
18:47consider is how much overlap there is between what you're already doing in SEO and what each platform
18:53rewards. If you're already ranking well in Google, you have a natural head start with AI overviews
18:58and Plexity. So, why not lean into it? 76% of AI overview citations used to come from pages already
19:06in Google's top 10. And I say used to because that number has dropped. A more recent study shows it's
19:12now closer to 38%. Which is still a lot. AI overviews are increasingly pulling from pages
19:18outside the top 10, including YouTube and Reddit. So, the connection between Google rankings and AI
19:23citations is weakening. Chat GBT is much more interested in publisher authority and editorial
19:30content. So, if your brand gets mentioned on Forbes, in a Reddit thread, or on a niche
19:35review site, that might matter more for ChatGpt visibility than your own pages Google ranking.
19:42And here's something a lot of people miss. Many of the top sighted domains in AI search don't get any
19:47traditional search traffic at all. AI visibility is its own game. Now, if you want to see the top
19:54domains for a specific platform, you can check that in HR brand radar. Just run a blank search
19:59and go to the cited domains report. Then you can filter using your desired AI platform.
20:04What you'll typically see is that the websites citing your brand are different on each platform.
20:10A domain that shows up heavily in AI overviews might barely appear in ChatGBT and vice versa.
20:15This is why a one-sizefits-all approach to AEO doesn't work. Now, the good news is you don't
20:21need to build completely separate strategies for each platform. A lot of the fundamentals,
20:26creating quality content, earning mentions, building topical authority help across the
20:31board. But knowing where each platform pulls from helps you prioritize your efforts. For example,
20:38if chat GBT is a big traffic driver for your niche, you'd want to focus on getting mentioned
20:43on high DR editorial sites and publishers. If AI overviews matter more, YouTube and Reddit should
20:49be on your radar. We'll get into these specific strategies in modules 2 and three. But for now,
20:54the key thing to understand is that each platform is its own ecosystem with its own rules. Now,
21:01before we actually start optimizing for AI search, there's something else you need to understand.
21:07What does winning an AI search even look like? Because it's not just about getting a link or
21:13a mention. So, in the next lesson, I'm going to break down the different types of AI visibility
21:18and why some of them might be more valuable to you than others. See you in the next lesson.
21:23Hey, it's Samo and welcome to the third lesson in module one. Now, in the last two lessons,
21:27I covered how AI search engines find and site content and how each platform works differently.
21:33But there's a question we haven't answered yet. What does winning in AI search actually look like?
21:39Because most people hear AI visibility, and they think it means one thing,
21:44getting a link in an AI response. But that's just one piece of the puzzle. And honestly,
21:49it might not even be the most valuable piece for your business. So, in this lesson,
21:54I'm going to break down the different types of AI visibility, show you the data on how
21:58often each one actually happens, and help you figure out which type matters most for you.
22:04Let me walk you through the three types of AI visibility, and I want you to think about which
22:08one applies to your business as I go through each. The first is cited and linked. This is the one
22:14everyone thinks about. AI includes a link to your page and its sources. The user can click through
22:19and land on your site. This is the best case for direct traffic and it's the easiest to measure.
22:24The second is mentioned but not linked. AI says your brand in its response but it
22:29doesn't give the user a link to click. You don't necessarily get the direct traffic or any traffic
22:35but the user now knows your name. And if they're interested, what are they going to do?
22:40They're going to search for you. This is basically a word of mouth recommendation at scale.
22:44And the third is not visible at all. AI doesn't mention you. It doesn't link to you. you're just
22:50not in the conversation. And this is actually important to know because you can't fix what you
22:55don't know is broken. Now, here's the thing. Most people assume that when AI mentions your brand,
23:00it's probably including a link. Well, not exactly. On average, only about 28% of AI mentions include
23:07a link. That means roughly seven out of 10 times your brand comes up in an AI response, there's no
23:13link attached. And it varies a lot by platform. Perplexity is the most generous, about 51.6 6% of
23:20mentions get a link. AI mode is around 36.8%. Chat GBT is at 26.9% and AI overviews only 10.7%.
23:30So if you're mostly tracking AI overviews, almost nine out of 10 times your brand shows up, there's
23:36no link. Now, you might think that means most AI visibility is low value since there's no click.
23:43But here's something that might surprise you. When we weighted these mentions by search volume,
23:47basically how many people are likely asking similar questions, the ones that do include a link
23:54tend to appear on much higher traffic queries. For example, on Perplexity, links show up in about 78%
24:01of total impressions, even though they're only in 51% of individual mentions. On Gemini, it's even
24:08more dramatic. Links appear in 71% of impressions despite being in only 16.8% 8% of mentions.
24:16So, the takeaway here is this. Citations are relatively rare, but when they happen,
24:21they tend to happen on the ones with the most eyeballs. But that doesn't mean unlin mentions
24:26are worthless. Far from it. Think about how LLMs actually work. They learn by reading the web.
24:32And every time your brand name appears on a credible site connected to a specific topic,
24:37that becomes another training example. The more the model sees your brand associated with a topic,
24:42the more confidently it mentions you when someone asks about that topic. It's like when you hear
24:47peanut butter, you think jelly. Or when you hear Tesla, you think electric cars. LMS build these
24:53same associations. And unlin mentions are what feed them. And there's real data to back this up.
24:59In a study of 75,000 brands, branded web mentions had the strongest correlation with AI visibility,
25:06a 0.664 664 correlation with showing up in AI overviews that's stronger than backlinks,
25:12domain rating, referring domains, or any other traditional SEO metric.
25:17So even when AI doesn't give you a link, just being mentioned is building your brand's presence
25:22in the model. It's the long game and it compounds over time. Now, there's another layer to this.
25:28Not all AI responses look the same and the type of response matters for your business.
25:34For example, some queries trigger step-by-step guides like how to fix a leaky faucet,
25:38how to set up Google Analytics, and if you're a service-based business or you create how-to
25:43content, these can be opportunities if you can get AI to recommend you as an expert. Then you
25:48have direct answers like what's the capital of France? If you're a publisher orformational brand,
25:54being the source AI sites for factual answers can build massive authority, but you probably
26:00won't get a click from these since AI gives the answer directly. And then there's video citations.
26:05We covered this in the last lesson. YouTube is one of the most cited domains across AI platforms.
26:11And if you're a creator, your videos can show up directly in AI responses. And some people prefer
26:16watching videos over reading text. So here's what I want you to take away from this lesson.
26:21AI visibility isn't binary. You're not just visible or invisible. It's a spectrum.
26:28And the type of visibility that matters most depends entirely on your business. If you sell
26:33a product, you want your brand showing up when people ask about your category. For example,
26:38a query like best golf balls surfaces tons of different brands and models and someone
26:44can literally click through from the AI response, land on a shopping result or the manufacturer site
26:49and buy something right away. That's a citation doing real work. If you're a publisher or
26:55content creator, training data visibility is your long gate. Every article AI cites,
27:00every video it surfaces reinforces your authority in the model. And if you're not yet visible, well,
27:07that's why you're taking this course. Now, if you want to see where you stand in AI search, go to
27:12HS brand radar and search for your website. And right away, you'll see how you stack up against
27:18competitors across different AI platforms. And you can filter by mentions, which are when your brand
27:23is named but not linked. citations, which is when AI actually links to your site, impressions, and
27:29share a voice. The gap between your impressions and your mentions is your opportunity. If AI is
27:35responding to queries about your topic, but not naming you, that's exactly where you need to
27:40focus. And that's exactly what we'll be covering in module 2, where we'll cover AEO, strategy,
27:46research, targeting, and gaps. I'll see you there. Hey, it's Ammo and welcome to the second
27:52module in our AI search course. Now, in module one, we covered how AI search actually works,
27:57the mechanics, the platforms, and what winning AI visibility looks like. In this module, I'm going
28:03to walk you through an AEO strategy that works in two phases. First, we'll assess where your
28:07brand stands today, figuring out exactly where the gaps are. Then, we'll move on to discovery,
28:13where we'll find the keywords and prompts people use to get information related to your business.
28:18So, let's start with step one, assess. In this lesson, I'm going to walk you through
28:22how to run a brand gap analysis. A brand gap analysis measures the difference between where
28:27your brand should be showing up and where it actually is. So, this is in Google search,
28:32AI results, and basically across the web. It examines everything shaping your discoverability
28:37and reputation from how AI describes you to which competitors are cited instead of you. So,
28:44the first step in this analysis is to map out your branded entities. Before you can find your gaps,
28:49you need to get clear on what you're actually measuring. And here's the thing, your brand gets
28:54referred to differently by different people. So, you want to map out your main brand name,
28:59any subbrands, product names, proprietary features, proprietary metrics, and even personal
29:05brands associated with your company. For example, at Hrefs, we'd map out the main brand, Hrefs,
29:11product brands like Site Explorer, Brand Radar, and AI content helper, proprietary metrics like
29:16domain rating and traffic potential, and personal brands like Tim Solo, Patrick Stocks, Ryan Law,
29:23and Glenn Alaw. Each of these has its own visibility profile in search and AI results.
29:28And you can repeat the analysis I'm about to show you for each one. Once you have your list, connect
29:33each entity to the topics and attributes people should associate with it. Search engines and LLMs
29:39don't understand brand names on their own. They infer meaning from how your brand is described and
29:44discussed. So, you need to clarify what problems you solve, what qualities you're known for,
29:50and what context you belong in. A quick way to do this is keyword research. Look for recurring
29:55adjectives, modifiers, and descriptive phrases people use alongside your brand
29:59or category. things like affordable, AI powered, enterprisegrain, whatever applies to your space.
30:06This gives you your benchmark for what your brand should be known and found for. Now, let's move on
30:11to the second step, which is to run your audit in hres. Start by entering your brand's website into
30:16site explorer. You'll get a dashboard of baseline metrics, domain rating, referring domains,
30:21organic keywords, organic traffic, and traffic value. This gives you your traditional SEO
30:26snapshot. But what we really care about in the context of AEO are the AI citation metrics which
30:32give you a snapshot of your brand's visibility in AI search across different platforms.
30:37Clicking into any of those takes you to the brand radar report for that platform which is where the
30:42real audit happens and there are four key things to pay attention to. First are mentions which are
30:47the number of times your brand is mentioned in AI responses. Then we have citations which
30:53are the number of times your website is actually cited as a source. impressions, an estimation of
30:58exposure based on how often responses containing your brand are shown, and AI share a voice,
31:04how often your brand is mentioned compared to your competitors. Now, the real power of Brand Radar is
31:10in its filters. This is where you can isolate the exact scenarios that matter. For example, you can
31:15filter for prompts that mention your brand name in the AI platform of choice. You can filter for
31:20responses that mention your brand but don't site your website. Those are miscitation opportunities.
31:27You can also add a competitor and then filter for queries where they're mentioned but you're not.
31:32And you can look at specific topics to see whether AI associates them with your brand
31:36or someone else's. Now take note of these numbers and let's move on to the third step which is to
31:42identify your gaps. When you're looking at this data, it helps to think about your gaps across six
31:47dimensions. And this is a framework Despina from Atro's laid out in her brand gap analysis guide.
31:52The first is your visibility gap. This is where your brand appears less often than competitors in
31:57search or AI results. The second is your narrative gap. This is how AI or media describes your brand
32:03versus how you actually want to be positioned. For example, maybe you're a premium tool, but AI
32:09keeps calling you a budget alternative or your key differentiator just isn't coming through. Third
32:15is your topic gap. These are topics you should be associated with but aren't. Like if you're a
32:20project management tool, but AI never mentions you when people ask about remote team collaboration.
32:26That would be a topic gap. Fourth is your format gap. AI tends to site certain types of content,
32:32guides, videos, reviews, comparison pages, and if you're not producing them, that's a gap. For
32:38example, in module one, we talked about YouTube being one of the most cited domains. And if your
32:43competitors have YouTube content getting cited and you don't, then you've got a content format gap.
32:48Fifth is your web mentions gap. These are external sources, listicles, review sites,
32:53forums, publications that mention competitors but not you. And as we covered in module one,
33:00those third party mentions are one of the strongest signals for AI visibility. And sixth
33:06is your demand gap. These are branded queries or searches that signal awareness opportunities you
33:11haven't captured. People are searching for things in your space, but your brand name never comes up
33:17alongside those searches. Now, when you look at all six together, you get a complete picture of
33:23your brand's visibility in AI. Not just how often you show up, but whether you're showing up for the
33:28right things in the right way in the right places. So, as you do your brand audit in step two, it's
33:36worth adding your prompts to these buckets. And it'll set you up perfectly for the fourth step,
33:42which is to prioritize. You're going to find a lot of gaps, and you can't fix everything at once. So,
33:47you're going to have to prioritize your efforts. You're generally going to do one of three things.
33:53Fix, which is improving or optimizing something that already exists. you're going to build, which
33:58is creating new content or pages for opportunities you're not covering at all, or influence, which
34:05is strengthening your off-site visibility through outreach and brand mentions. And you want to weigh
34:11each opportunity by asking, "How much demand could this drive? Does it support your brand
34:15credibility? And does it improve your chances of being cited in AI?" Start with the quick ones.
34:22If you have a page that's already ranking but just needs a content update to close a topic gap,
34:27that's low effort and potentially high impact. If you're missing from a major listical that all your
34:33competitors are on, that's a web meions gap you can close with outreach. Now, as you go through
34:38this process, you'll probably find that most of your gaps fall into one or two of the buckets I
34:43mentioned before. And that's a good thing because it tells you exactly where to focus so you can
34:48create systems around them. and I'll walk you through how to close each type of gap in module 3.
34:54From creating content that gets cited to earning mentions from thirdparty sites to optimizing your
34:59YouTube presence. So the audit you do right now, it becomes your personalized road map for the rest
35:05of this course. Now, one more thing, you can do this exact same audit for your competitors to get
35:10a wealth of insights on new topics and gaps that will be relevant to your business. Look
35:16at their branded queries to see what users and AI connect to them more strongly than they do to you.
35:22Sometimes those are quick wins. You might already have the features, you just haven't created the
35:26content that connects them to your brand, or you don't have enough pages that are talking about
35:31that feature. We've put together a template you can use to organize all of this and share
35:36it with stakeholders. So, I'll link that in the description. Now, you have your baseline saved and
35:40a clear picture of where the gaps are. But knowing your gaps is only the first step. You also need to
35:46know what opportunities are out there. And keyword and prompt research for AEO is how you do it,
35:52but it's a bit different from what you might be used to. There are queries where AI dominates,
35:57queries where traditional SEO still wins, and a whole set of platforms most people
36:02aren't even thinking about. That's what we'll cover in the next lesson. I'll see you there.
36:07Hey, it's Ammo and welcome to the second lesson, which is on keyword and prompt research for AEO.
36:12Now, in the last lesson, I walked you through how to run a brand gap analysis, so you should have a
36:17clear picture of where your brand is showing up and where it isn't. Now, it's time to find the
36:22keywords and prompts to actually go after. And in this lesson, I'm going to walk you through
36:26the full keyword research process for both SEO and AEO. Why? Because there's a ton of overlap between
36:33the two. And half the battle is really identifying which is which and knowing how to approach them
36:39differently. So, the first step is to build your keyword list. And this part honestly hasn't
36:44changed that much. You still need two things. Seed keywords, which are broad terms related to your
36:49niche, and modifiers, which are add-ons like best or howto that turn those seeds into real searches.
36:56Now, a quick way to come up with these is to just ask your AI assistant of choice something like,
37:01I'm doing keyword research for my type of site, which makes money through my revenue model.
37:07My target audience is this group. Give me 10 seed keywords that are one to two words max
37:13and five plus modifiers that will help me surface appropriate content formats
37:18I can use in my keyword research. The seeds and modifiers should not share the same words.
37:24And just like that, you've got a solid list of seeds and modifiers to work with,
37:28but these are just the starting point. Take your seeds and paste them into keywords explorer.
37:33Then go to the matching terms report and add your modifiers using the include filter. And just
37:38like that, you should have hundreds, maybe even thousands of real keyword ideas your audience is
37:43actually typing into Google. Now, the second step is to vet those keywords because some of them are
37:49a trap. Some of these keywords are going to look incredibly enticing. High volume, high traffic
37:54potential, low difficulty scores, all the right metrics, but not all of them are worth targeting.
38:00Before you commit to any keyword, it needs to pass three tests. I call this the bid formula.
38:06B is for business potential. Ask yourself, if I rank number one for this keyword, does it
38:11actually help my business? A keyword like what is espresso has solid volume and low difficulty,
38:17but someone searching that isn't looking to buy anything, maybe ever. Compare that to best
38:23espresso machine under $500, where the searcher is showing intent and has a budget. Always choose
38:29keywords that move the needle. I is for intent. Google the keyword and look at what's actually
38:35ranking. If every top result is an e-commerce page and you're trying to rank a blog post,
38:40it's not going to happen. The SER tells you what searchers want. Match the intent or move on. And
38:47D is for difficulty. You need to choose keywords you actually have a chance at ranking for. Check
38:52the referring domains and domain rating of the top ranking pages. In general, the more links and the
38:57higher the DR, the tougher the competition. If you see a few low DR sites in the top 10, that's
39:03usually a good sign. If a keyword passes all three tests, you should consider targeting it. Unless,
39:09and this is where step three comes in, the AI filter. Before you commit to any keyword,
39:15there's one more question you need to ask. Can AI fully satisfy the user for this query?
39:22Because even if a keyword passes bid, if the AI overview is so good, there's no reason for
39:28anyone to click through, that keyword might be a trap. And there's hard data behind this.
39:34AI overviews appear on about 21% of all keywords, but for informational queries, it's much higher.
39:42Nearly 58% for question queries, 46% for queries with seven or more words, and 99.9% of keywords
39:49that trigger AI overviews areformational in intent. So before you commit to a keyword,
39:55Google it. Look at what shows up. Put yourself in the searcher shoe and ask, "Am I satisfied with
40:01this answer or do I need to click somewhere to learn more?" If the AI overview nails it,
40:07that keyword might not be worth targeting the traditional way. But here's the good news. Even
40:13though AI is eating clicks for a ton offormational keywords, there's a whole category of searches
40:18AI hasn't touched. Free tools, search backlink checker, no AI overview, mortgage calculator,
40:25nothing. Word counter, nothing. Why? Because when someone searches for a tool, they need to actually
40:32use something. AI can't replace that yet. To find these opportunities, go back to keywords explorer
40:38with your broad seeds. Head to the matching terms report and add modifiers like calculator, checker,
40:44generator, tool, template, finder, planner, and maker. These are all actionoriented queries where
40:51someone needs to do something. AI can't satisfy that yet. So the organic click is still there for
40:57the taking. You can also filter for transactional intent directly. Just choose transactional in the
41:02intent filter and you'll get queries where people are looking to buy, sign up or take some kind of
41:08action. Now the fourth step is to find your AI mention opportunities. A minute ago I said
41:13if the AI overview nails the answer, that keyword might not be worth targeting the traditional way.
41:21But that doesn't mean you ignore it. These keywords just need to be targeted differently.
41:25And that's where AEO comes in. Instead of trying to rank and earn a click, your goal is to get your
41:31brand mentioned in the AI response itself. And to do that, you need to know which queries to focus
41:36on and which pages AI is pulling from. Now, it helps to know what AI is actually citing.
41:42We studied this across AI overviews and chat GPT and found that 43.8% of all cited pages
41:49are listicles. And in my opinion, these pages show up so often because they help AI build consensus.
41:56So if your brand is mentioned across multiple lists, that's multiple sources recommending you
42:01and AI picks up on that. So to find the queries that matter for your brand,
42:06go to brand radar and enter your website. Find your brand, hover over the AI platform you
42:11want to research and click others only. This shows you that mention gaps where competitors
42:16are showing up but you're not. Then filter for queries containing best, top, versus, review,
42:23or alternative. And you'll see the queries where AI is mentioning your competitors but not you,
42:29and the ones AI is most likely pulling from when looking for brands in your space. This is your
42:34short list. Now, one thing to keep in mind, over 45% of citations change when AI overviews refresh,
42:42and that happens on average every 2 days. So, this isn't a one-time exercise. It's worth revisiting
42:48this report regularly to catch new queries as they come in. And that brings us to the fifth step,
42:54prompt research. When someone opens Chat GBT, Google AI mode, or Perplexity,
42:59they're not typing keywords. They're having conversations. They're saying things like,
43:03"I'm a small agency owner looking for a marketing platform. Which one should I choose?" Or,
43:08"What's the best way to track rankings if I'm just getting started?" They use natural language
43:13with full context and so every person phrases it differently. So you can't approach this the
43:19way you would keyword research where you find the exact terms and go after them one by one. With AI,
43:25the same question asked 10 different ways can get 10 different answers with 10 different brands
43:30mentioned. And on top of that, AI fans each prompt out into many sub queries behind the scenes,
43:37most of which have zero search volume and will never repeat. If you're invisible for a topic,
43:43it's not about optimizing for one specific prompt. It's about building visibility across that entire
43:50topic, which is exactly what we'll cover in module three. So, with your topic list and
43:54your prompt gaps mapped out, let's go and close those gaps. I'll see you in the next lesson.
44:01Hey, it's Ammo and welcome to the third module in our AI search course. In modules one and two,
44:06we covered how AI search works and how to find the keywords and prompts to go after.
44:11Now, it's time to actually execute. And that's what this module is all about. And in this first
44:16lesson, we're going to be talking about creating content that gets cited. And I've got some data
44:21on what AI actually sites to back our strategy. First, content length doesn't matter. We analyze
44:27over 174,000 pages cited in AI overviews and the correlation between word count and getting cited
44:34is just 0.04. That's basically zero. Over half of all cited pages, 53.4% are under a,000 words.
44:44So, if you've been writing 3,000word articles because you think longer content ranks better,
44:50that doesn't apply here with AEO. AI doesn't care how long your page is.
44:54It cares whether your page answers the question. Second, freshness matters a lot.
45:00Content cited by AI is on average 25.7% fresher than what ranks in traditional organic results.
45:07And when you look at chat GBT specifically, 89.7% of its top cited pages were updated in 2025.
45:14And get this, 76% were refreshed within the last 30 days. Think about that for a second.
45:21If your content hasn't been touched in 6 months, you're already at a disadvantage for AI citations.
45:28Now, this doesn't mean you should just change the publish date and call it a day. Google can detect
45:33that. You need to make meaningful updates to the actual content. We'll talk about how to do that
45:38later in this lesson. And the third data point is that format matters. If you remember from the last
45:43module, we talked about how 43.8% of all cited pages by chatbt are listicles. Best X, top X,
45:52comparisons, reviews. That's not a coincidence. These formats are built for AI because they give
45:58clear, structured recommendations that AI can pull from. But lists aren't the only format that work.
46:04Datadriven content with original stats also get cited heavily because AI loves citing specific
46:10numbers. And comparison content like X versus Y pages perform well because they map directly
46:17to how people ask AI questions. So, the key takeaway here is simple. Keep your content fresh,
46:24keep it focused, and lean into formats that AI can actually use. Now, let's talk about how to
46:30actually structure your content so AI can use it. And here's something a lot of people get wrong.
46:36They think they need to write differently for AI. Like, there's some special AI optimized
46:41format they need to follow. There isn't. You're writing for humans. AI is trained on what humans
46:47find valuable. So content that serves human readers well is content AI wants to site.
46:54That said, there are a few principles that help both humans and AI get more out of your content.
47:00The first one is bluff, which stands for bottom line upfront. This one's borrowed from military
47:06communication, and it's simple. Start every section with the answer, not the backstory.
47:12For example, instead of opening a section with, "Over the past few years, link building strategies
47:17have evolved significantly due to changes in how search engines evaluate link quality,"
47:22you could write, "The most effective way to build backlinks in 2026 is to create original research."
47:28Now, here's why this matters. When humans scan a page, they follow what's called an F pattern.
47:34They read the beginning closely, skim the middle, and maybe pick up again at the end. LLM show a
47:40similar pattern. They weigh the beginning and end of a passage more heavily than the middle.
47:45So if your key point is buried three paragraphs into a section, both humans and AI might miss it.
47:52So put the answer first, then support it with context and examples. The second principle to
47:57apply is atomic content. This means every section on your page should be able to stand on its own.
48:04So, when editing your content, ask yourself, if AI pulls just one section from your article,
48:10does it still make sense, or does it depend on context from three paragraphs earlier?
48:15This matters because AI systems chunk your content into pieces when they process it.
48:20Different AI models chunk content differently, and you can't control how they do it. But if every
48:26section is self-contained, it doesn't matter where the chunks fall because the meaning survives. A
48:32good test you can do is to take any H2 section on your page and read it completely out of context.
48:38If it doesn't make sense without the rest of the page, rewrite it so it does. The third principle
48:43is entity rich writing. AI understands text by looking at entities and the relationships between
48:49them. Entities are things like brands, products, people, places, and specific concepts. So instead
48:55of writing this tool helps with SEO, write HF's keywords explorer helps you find keywords with
49:01low difficulty and high traffic potential. By providing more entities, relationships,
49:06and context, AI has more to work with. And this also ties into how AI picks what to site.
49:13The more specific and concrete your content is, the more useful it is when AI is trying
49:18to answer a specific question. And the fourth principle is to keep it simple and declarative.
49:24Use short sentences and clear subject verb object structure. Basically, try to keep things to one
49:30idea per sentence. This isn't about dumbing down your content. It's about making it easy to parse
49:36for both people and AI. If a sentence takes two reads to understand, it's probably too complex.
49:43Simplify it. Your readers will thank you and AI will have an easier time extracting the key
49:48points. Now, these four principles will help you create content that's more likely to get cited.
49:53But there are a couple more things worth knowing that can push your chances even further.
49:58And the first is something most people don't think about. LMS have a tendency to flatten originality.
50:04Like if you come up with an original concept or framework and you're the only one talking
50:09about it, AI will often absorb the idea without crediting you. It becomes part of its general
50:15knowledge. The way around this is to label your ideas with your brand name. For example, instead
50:21of calling something a content scoring matrix, call it the HF's content scoring matrix or your
50:26brand content scoring matrix. Define it explicitly and then distribute it widely across your blog,
50:33social media channels, podcasts, Reddit, etc. The more places it shows up with your name attached,
50:40the harder it is for AI to flatten it into generic knowledge. Now, another thing you
50:45can do is refresh what I call sleeper pages. These are pages on your site that used to rank well but
50:51have slowly declined over time. They already have the back links. They already have the authority.
50:57They just need a refresh. And because freshness is such a strong signal for AI citations,
51:03updating these pages can be one of the fastest ways to gain AI visibility. Here's how to find
51:08them. Go to site explorer and enter your domain and head to the top pages report. Then sort by
51:13traffic change and look for pages with significant declines. What you're looking for are pages that
51:19have two things. A decent number of backlinks, which means they already have authority,
51:24and a clear traffic decline, which usually means the content has gone stale. Now, before you update
51:30anything, make sure it's actually a content issue and not a backlinks issue. If the page never had
51:35many referring domains to begin with, updating the content probably won't help. But if it has
51:41links and the content is just outdated, that's a high potential opportunity. So now you know how to
51:47create and update content that AI actually wants to site. But creating great content is only half
51:52the equation. You also need to get mentioned on other people's content, the pages AI is already
51:58pulling from. And that's exactly what we'll cover in the next lesson. I'll see you there.
52:03Hey, it's Samo and welcome to the second lesson in this module, which is on earning mentions
52:07and citations. Now, in the last lesson, we talked about creating content that gets cited. But here's
52:13the thing. A lot of AEO isn't about what's on your site. It's about getting mentioned on other
52:19people's pages. And not just any pages, the ones AI wants to pull from. Branded web mentions are so
52:25important that in our study of 75,000 brands, they had the strongest correlation with visibility in
52:31Google's AI overviews, stronger than backlinks, referring domains, and even domain rating. So,
52:37in this lesson, I'm going to show you the three types of pages you should be getting mentioned on
52:41and how to find the ones that matter most. Let's get started. So, I like to think about mention
52:46sources in three tiers. And the reason I use tiers is because not all mentions are created equal.
52:52Where you get mentioned matters just as much as how often you get mentioned. According to our
52:57data, we found that getting mentioned on highly linked pages has a 0.7 correlation with appearing
53:03in Google's AI overviews. That's even higher than the general branded mentions correlation.
53:08So, the quality of the page you're on makes a huge difference. Now, let's talk about tier one
53:13mentions, which are found in third-party editorial content. These are the hardest mentions to earn,
53:18but they're also the most valuable. Think industry publications, review sites like
53:23Wire Cutter or Techraar, listicles and comparison posts on authoritative blogs, and YouTube reviews
53:29from creators in your space. Why are these so powerful? because they're exactly the kind of
53:34pages AI loves the site. Remember, 43.8% of Chat GPT citations are listicles and comparison pages.
53:43So, if you're mentioned on those pages, you're in the pool of content AI is already pulling from.
53:49Now, to find the right pages to go after, go to brand radar and enter your domain.
53:53Then, open the cited domains report. This shows you the top websites that AI is citing for topics
53:58related to your brand. You'll see the number of AI responses, the number of pages, and how often
54:04each brand is being mentioned. From here, you can identify which sites matter most for your niche.
54:10Maybe it's kbb.com for cars or cnet for tech or specific niche blogs in your industry. These
54:16are the sites where getting a mention can directly lead to AI visibility. Now, it's important to note
54:22that you don't have to wait for AI to start citing a page before you try to get on it. Instead, look
54:28for pages that already have a lot of links and cover your topic. Even if they're not cited now,
54:33there's a good chance that they'll be cited at some point. You can use content explorer for this.
54:39Search for your title and add title colon best or title colon versus along with a minus operator
54:46before your brand name. This will surface listicles and comparison posts in your niche
54:50where your brand isn't mentioned. Then filter for pages with a good number of referring domains.
54:57Next up are tier 2 mentions which can be found on user generated content and community platforms.
55:03This includes Reddit, Quora, niche forums and community sites,
55:07and these matter more than you might think. Reddit is one of the most frequently cited sources by
55:11Chat GBT. It's also one of the foundational training sources for large language models.
55:16The play here isn't to spam Reddit threads with your brand name. That'll backfire fast. Instead,
55:22find threads where people are asking questions your product or expertise can genuinely answer.
55:28If someone's asking what's the best tool for X and your product is actually a good fit,
55:33contribute a real answer. You can find these threads through brand radar as well. Look at
55:38the cited domains report and see if reddit.com shows up for your space. If it does, dig into
55:43which specific threads AI is pulling from and join the conversations that are already happening.
55:49Now, if you want to find niche specific Reddit pages that are already ranking well in Google,
55:54you can go to site explorer, enter reddit.com, and open the organic keywords report.
55:59Filter for keywords ranking in the top five, and add your niche terms to the include filter.
56:05And now you've got a list of Reddit pages that are already ranking well in Google and are related to
56:10your space. And you can do the exact same thing for niche forums and Q&A sites. Wherever your
56:16target audience is having conversations about problems that you solve, that's where you want
56:20to be present. Finally, we have tier three, which are your own properties. Some brands own multiple
56:26domains. At for example, has detail.com and blogger genen. If these properties
56:31are authoritative in their own right, they can serve as additional citation sources for AI.
56:36Now, even though you don't have the resources to run multiple sites, the principle still applies.
56:42Your YouTube channel, your podcast, your LinkedIn content, these are all indexed and can all show
56:48up as sources AI pulls from. Basically, the more places your brand appears in a positive topically
56:54relevant way, the more training examples AI has to learn from. Now, earning mentions is one thing,
57:00but you also need to keep track of them because mentions can disappear. pages get updated, lists
57:06get refreshed, and your brand can get removed without you ever knowing. And on the flip side,
57:12sometimes AI picks up wrong information about your brand from outdated or inaccurate sources.
57:18So, it's worth doing a regular mention audit. In Brand Radar, you can track your overall mention
57:23trends over time. Look for any drops in mention volume. If you find a page that was previously
57:29mentioning you, but your brand was removed during an update, that might be worth investigating. And
57:34pay attention to sentiment, too. Are AI responses about your brand accurate? Are they positive?
57:40If you spot misinformation, your best move is to update your own content first and then reach
57:46out to the publisher to request a correction. The faster you fix inaccurate mentions, the
57:52less time AI has to learn from them. So, between this lesson and the last one, you've got a clear
57:57playbook for earning AI visibility through content and mentions. But there's one platform we haven't
58:03talked about yet that deserves its own lesson, and that's YouTube. I'll see you in the next lesson.
58:08Hey, it's Ammo and welcome to lesson three, which is on YouTube optimization for AI visibility. Now,
58:14in the last two lessons, we covered how to create content that gets cited and how to earn mentions
58:19on other people's pages. But there's one platform that deserves its own conversation, and that's
58:24YouTube. Why? Because YouTube is the most cited domain in Google's AI overviews. And get this,
58:32according to our data, YouTube mentions have a 0.737 correlation with chat GBT visibility.
58:39That's the strongest correlation of any factor we study. And there's a reason for that. GBT4
58:45was trained on over a million hours of YouTube transcripts. So YouTube isn't just a platform
58:51AI sites, it's a platform AI learns from. So, in this lesson, I'm going to walk you through
58:56a three-step process to get your YouTube videos in front of AI. Let's get started.
59:02So, the first step is to find what's already working on YouTube in your niche. And the key
59:07idea here is that you want to target what I call search hits rather than viral hits. A viral hit
59:13can get you a spike of views and it can keep spreading based on a YouTube user's interests.
59:18But once the YouTube algorithm has exhausted the interested people, it dies. a search hit.
59:24It gets you consistent traffic from both Google and YouTube search month after month because
59:29people are actively searching for that topic. And search hits are exactly the kind of videos AI is
59:35likely to pull from. And that's because if Google is already ranking a YouTube video for a keyword,
59:40there's a good chance AI overviews will site it, too. On top of that, titles for search videos
59:46tend to be very clear about what the video is about, whereas viral hits, not so much. So,
59:52here's how to find these topics. Go to site explorer and enter www.youtube.com/watch.
59:58Then, open the organic keywords report. This shows you every keyword that YouTube videos are ranking
1:00:03for in Google. Now, filter for keyword rankings in the top three and add your niche terms to
1:00:08the include filter. What you'll get is a list of topics where YouTube videos are already ranking
1:00:14at the top of Google and are related to your space. Now, let's move on to the second step,
1:00:19which is to actually create videos that rank. Once you found your topics, you need to make
1:00:24sure your video is set up to rank in Google. And there's a checklist I follow for this. First,
1:00:30your title needs to contain the keyword people are searching for. This isn't the place for clever or
1:00:34clickbaity titles. If the keyword is how to use Google Docs, that should be right in your title.
1:00:41Save the creativity for the thumbnail. The title handles the keyword. The thumbnail
1:00:46sells the click. Second, your description needs to be a real summary of the video. Just write a
1:00:51summary of what your video covers and add your target keyword in the first couple of lines.
1:00:56Google reads this, AI reads this, and viewers read it, so make a count. Third, add timestamps.
1:01:04Timestamps turn into YouTube chapters, and those chapters can show up in Google for specific
1:01:09queries. So, if your video covers five tips and someone searches for tip number three, Google
1:01:15can link directly to that chapter. It's basically free extra visibility for like 2 minutes of work.
1:01:22Fourth, say the keyword in your video. And this one's important. Google understands audio.
1:01:27Liz Reed, who's VP of search at Google, has said that Google can understand audio content
1:01:32and video content. So, if your video is about the best protein powder for repair,
1:01:37actually say those words in the video. Don't put it in the title and hope for the best. And fifth,
1:01:43match the format to what's already ranking. If tutorials are dominating the search results
1:01:47for your keyword, make a tutorial. If listicles rank, make a listicle. Don't fight the format.
1:01:54Look at what's working and match it because you're matching the intent of the searcher.
1:01:59Now, none of this is complicated, but it's the difference between a video that gets buried and
1:02:04a video that shows up every time someone searches for that topic. And that brings us to the third
1:02:09step, which is to layer in AI visibility. So, at this point, you've got a video that's optimized
1:02:15for Google search. But here's where you take it a step further for SEO. Go to Brand Radar and enter
1:02:20a popular brand or YouTube channel and go to the topics report. Then set a filter where the domain
1:02:25mentioned is YouTube.com. Now, you can see exactly which queries AI is pulling YouTube videos into.
1:02:32So, go and create content around those topics. And as for how to actually rank there, it comes
1:02:37back to what we already covered, pick the right keyword, make a thorough, well optimized video,
1:02:43and be comprehensive without wasting people's time. And here's one more thing to keep in mind.
1:02:49Remember, every video you publish on YouTube is potentially training data for AI models.
1:02:55So even if a video doesn't get cited right away, the content is being absorbed. The more helpful,
1:03:02specific, and well ststructured your videos are, the more likely AI is to learn from them
1:03:07and eventually recommend them. So, that covers content mentions, and YouTube, but there's
1:03:12a technical side to AEO that most people skip entirely. Things like structured data, robots.txt,
1:03:19and making sure AI can actually access your site in the first place. And that's what we'll cover in
1:03:24the next lesson. I'll see you there. Hey, it's Samo and welcome to the fourth lesson in this
1:03:29module, which is on the technical side of AEO. Now, I know technical can sound intimidating,
1:03:35but this lesson isn't about rewriting your site's code. It's about making sure that AI can actually
1:03:41access and understand your content. And while access and understand might sound rudimentary
1:03:46for some of you, the reality is a lot of sites are accidentally blocking AI without even knowing it.
1:03:54According to our data, around 5.9% of 140 million websites are blocking GBTO, which is
1:04:01Open AI's crawler. That's millions of sites that are invisible to ChatGBT. So, in this lesson, I've
1:04:08got six technical checks and tips for you to make sure AI can find you so that it can promote you.
1:04:15Let's get started. So, the first thing you need to check is your robots.txt file.
1:04:19Robots.txt txt is a file on your site that tells crawlers what they can and can't access.
1:04:26And the thing is, it's not just Google's crawler you need to think about anymore. There are now
1:04:30dozens of AI specific bots that crawl the web. The main ones you should know about are GPTbot
1:04:36and OAI searchbot from OpenAI, Claudebot from Anthropic, and Google extended from Google. If
1:04:43any of these are blocked in your robots.txt, txt, you're asking those AI platforms not to crawl your
1:04:50content. And assuming they obey your rules, they sure won't be recommending your pages then if they
1:04:55don't know what's on them. Now, you might not have blocked these bots intentionally, but a lot of
1:05:00sites inherit robots.txt rules from templates or old configurations, and some platforms add blocks
1:05:07by default. For example, Cloudflare has a feature called instruct AI bot traffic with robots.txt.
1:05:15That's now enabled by default. When this is on, Cloudflare automatically updates your robots.txt
1:05:21to signal that your content shouldn't be used for AI training. So, if your site is on Cloudflare,
1:05:27you could be blocking AI crawlers without even realizing it. So, the first step is simple. Go to
1:05:33your doommain.com/root.txt and look for any lines that mention GPTbot, Claudebot, Google extended,
1:05:41or OAI searchbot. If you see a disallow rule next to any of those, you're blocking that AI crawler.
1:05:48You can also use HF site audit to check this. Run a crawl on your site and it'll flag any robots.txt
1:05:54rules that might be blocking AI crawlers. Now, while we're on the topic of files AI reads,
1:05:59I want to make a quick note on something you might have heard of called LLM.txt.
1:06:04This is a proposed standard kind of like robots.txt, but specifically designed to
1:06:09tell AI systems about your site. The idea is that you create a file atyoudommain.com/lms.txt
1:06:17that gives AI a summary of who you are, what your site covers, and where to find your most important
1:06:24content. It's useful in theory, but as of right now, no major LLM provider officially supports it.
1:06:31OpenAI doesn't use it. Anthropic publishes one on their own site, but hasn't confirmed their
1:06:36crawlers actually read it, and Google hasn't adopted it either. So, should you create one?
1:06:43Well, I don't think it'll hurt you, but I wouldn't prioritize it over the other things we've talked
1:06:47about in this lesson. Robots.txt is still the file that actually matters most right now.
1:06:53All right, the second thing to check is how your site handles JavaScript. Some AI platforms can
1:06:58render JavaScript and some can't. Without getting too technical, Gemini and Copilot can render JS
1:07:04while ChatGpt's crawler does not. So if your content relies on JavaScript to load,
1:07:09which is common with single page apps and some React or Angular frameworks, ChatGBT
1:07:14literally can't see your content. It visits the page and gets an empty shell. The fix here
1:07:20is serverside rendering, which means your server sends the fully rendered HTML to the crawler
1:07:26instead of relying on JavaScript to build the page in the browser. If you're already doing this for
1:07:31SEO, you're covered. If not, it's worth looking into, especially if AI visibility matters to you.
1:07:38A quick way to test this is to disable JavaScript in your browser and visit your own site.
1:07:43If the content disappears, you have a JavaScript rendering issue that's affecting AI crawlers, too.
1:07:49The third thing to consider is page speed. Now, you might be thinking, page speed is an SEO thing,
1:07:54not an AEO thing, but it can actually matter more for AI retrieval than for traditional search.
1:08:02When AI systems retrieve information in real time, they're fetching, parsing,
1:08:07and chunking your pages on the fly. And if your page takes too long to load,
1:08:12it can get dropped before it's even scored. So, it won't be making it into an AAI response,
1:08:17even if the content is great. The good news is that if you've already optimized your core web
1:08:22vitals for SEO, you're most of the way there. Fast loading pages with clean HTML benefit both Google
1:08:29and AI systems. And that brings us to the fourth tip. Create clean HTML structure.
1:08:35This one's straightforward. AI systems parse your content by following your HTML structure. So,
1:08:41if your headings are logical, your sections are well organized, and your paragraphs are focused
1:08:46on one idea each. AI has an easier time extracting the right information. This ties directly back to
1:08:53the content principles we covered in lesson 3.1, bluff, atomic content, and entity rich writing.
1:09:01Those principles aren't just about writing style. They're about making your content technically
1:09:06parsible for AI. So, when you're structuring your pages, use proper heading hierarchy.
1:09:11H1 for the title, H2s for the main sections, and H3s for subsections. And make sure each section
1:09:18can stand on its own because AI might chunk your content at any heading boundary. The fifth tip
1:09:24is about schema markup. Schema markup, which is also called structured data, is code you add to
1:09:30your pages to help search engines understand your content. Things like article schema, FAQ page,
1:09:36how-to, and local business. Now, does it help with AEO? Honestly, the evidence is mixed. There's
1:09:44no confirmed data that adding schema directly improves your chances of being cited by AI, but it
1:09:51doesn't hurt. And if you're already using it for SEO, there's no reason to remove it. I wouldn't
1:09:56spend a ton of time on schema specifically for AEO, but if you're setting up a new page, adding
1:10:02the right schema types is a good habit that makes your content easier for any system to understand.
1:10:08All right, the sixth tip that I have for you is to optimize for AI hallucinated URLs. AI
1:10:13assistants sometimes make up URLs that don't exist on your site. They'll recommend a page to a user,
1:10:19the user clicks it, and they hit a 404 error. And this happens a lot more often than you'd expect.
1:10:26According to our data, AI assistants send visitors to 404 pages 2.87 times more often than Google
1:10:34search does. And Chat GPT is the biggest offender with about 1% of its clicked URLs leading to 404
1:10:41pages. Now, rather than letting that 404 be the end of a visitor's browsing journey,
1:10:46you should either fix or optimize those pages to get more out of them. You can do that by checking
1:10:51your analytics for pages that are getting traffic from AI referers but returning a 404 status.
1:10:57If you spot a hallucinated URL that's getting consistent traffic, set up a redirect to the most
1:11:02relevant real page on your site. That way, you're capturing traffic that would otherwise be lost.
1:11:08Now, while creating content and getting cited is a big part of AEO, it's only part of the picture.
1:11:14You also need to know if it's actually working. And that's exactly what we'll be covering in
1:11:19module four, which is all about measuring and tracking your AI visibility. I'll see you there.
1:11:25Hey, it's Samo and welcome to module four in HF's AI search course. Now, in module three,
1:11:30we covered how to create content, earn mentions, and optimize YouTube videos to get mentioned and
1:11:36cited in AI search. And we also talked about how you can optimize for the technical side of AEO.
1:11:42So, now you've got a playbook for execution. But here's the thing. None of that matters
1:11:48if you can't measure whether it's working. And that's what this module is all about. Now, I'll
1:11:53be upfront with you. Measuring AI visibility is a lot harder than measuring results from traditional
1:11:58SEO. With SEO, you've got Google Search Console giving you impressions, clicks, and rankings.
1:12:04With AI search, a lot of that data either doesn't exist or is hidden from you. But that doesn't mean
1:12:09you're flying blind, because there are three ways to track your AI visibility. And in this lesson,
1:12:15I'm going to walk you through how to set each one up. Let's get started.
1:12:19So, the first thing you should track is AI referral traffic to your site. This is when
1:12:23someone clicks a link from Chat GPT, Perplexity, Claude, or another AI platform and lands on your
1:12:29site. In analytics tools like Google or HF's web analytics, it'll show up as a referral visit.
1:12:35This is helpful in knowing how many people are finding you because of AI. But here's where it
1:12:40gets tricky. Not all AI platforms pass referral data properly. Some of them strip it out entirely,
1:12:47which means the visit shows up as direct traffic in G4. And if it does that, then there's no real
1:12:53way to know that the traffic came from AI. For example, ChatGpt source links in search results
1:12:59pass referral data properly. But incontent links on paid accounts use a no referral attribute,
1:13:05so those visits are actually invisible. Claude tracks properly. Perplexity tracks on the web
1:13:11but not on its desktop app. Copilot tracks on the web but not on Windows. And Grock doesn't pass
1:13:17referral data at all. So the key takeaway here is this. Use AI referral traffic to understand the
1:13:24general trend of which AI platforms are sending you customers and visitors. But understand
1:13:30that what you see in your analytics is likely an undercount. Now with that caveat out of the way,
1:13:39let me show you how to set this up. If you're using G4, you'll want to create a custom channel
1:13:41group that isolates AI traffic. Go to admin, then data display, then channel groups. Copy
1:13:48your default channel group, and add a new channel called AI traffic. Then set the source to match a
1:13:53reax that includes chatgpt.com, perplexity, gemini.google.com, copilot.microsoft.com,
1:14:01claw.ai, and deepseeek.com. Once that's set up, go to reports, then acquisition, then traffic
1:14:09acquisition, and select your new channel group. Now you can see the traffic AI is sending you,
1:14:14the pages it's directing people to, and how those visitors behave compared to other channels.
1:14:20Now, if you want something simpler than G4, Hrefs has a free tool called Web Analytics that does
1:14:26this automatically. It has a built-in AI search channel, so you don't have to set up any custom
1:14:31groups. It also separates unknown traffic from direct traffic, which J4 doesn't do.
1:14:38That means you can get a clearer picture of where your traffic is actually coming from.
1:14:42All right, so once you've got AI traffic set up, there are two things I'd pay attention to. First,
1:14:47look at which pages are getting AI traffic. These are the pages AI is already recommending to users.
1:14:53Make sure you keep these up to date, keep them accurate, and have clear calls to action. If AI is
1:14:58sending people to a page that hasn't been updated in a year, it'll probably stop sooner than you'd
1:15:04like. And second, look at your important pages that aren't getting AI traffic. If you've got a
1:15:10key product page or a highv value blog post that's getting zero AI referrals that should be getting
1:15:16it, that's worth investigating. It could be a content issue, a crawling issue, or it could just
1:15:21mean AI isn't surfacing that topic yet. The second thing to track is AI bot activity on your site.
1:15:28This one's a bit different. Instead of tracking the humans who click through from AI, you're
1:15:33tracking the AI bots themselves, the crawlers that visit your site to read and index your content.
1:15:39And here's something most people don't realize. AI bots visit your pages far more often than humans
1:15:46do. So, the pages they're hitting the most are likely your strongest citation candidates. Now,
1:15:51there are two types of AI bots to know about. The first type is training bots like GPTbot and Google
1:15:57extended. These take your content and use it to train AI models. The second type is search and
1:16:03citation bots like ChatGpt user and OI search bot. These fetch your pages in real time when
1:16:10a user asks a question. These are the ones that can actually drive referral traffic to your site.
1:16:16To track bot activity, you can use server logs if you have access to them. But the easier way is
1:16:20through HF's bot analytics, which has a Cloudflare integration that shows you exactly which AI bots
1:16:26are visiting your site, how often, and which pages they're focusing on. And this works with
1:16:31a free Cloudflare plan, too. Now, what you're looking for here are patterns. If a citation bot
1:16:36is hitting a specific page repeatedly, that page is likely being used as a source in AI responses.
1:16:43And if there are important pages that bots aren't visiting at all, that could mean they're hard to
1:16:48discover, which ties back to the internal linking and site structure we talked about in module 3.
1:16:54All right, the third thing to track is self-reported attribution. This one's the simplest
1:16:58to explain, but it might be the most important for proving the value of AEO to your team
1:17:04and to your clients. You see, a lot of the impact of AI visibility doesn't show up in your analytics
1:17:09at all. Someone asks ChatGBT for a recommendation. They get your brand name, then they go to the
1:17:14browser bar and they type it directly in there. That shows up as direct traffic or they Google
1:17:19your brand name after hearing about you from AI. That's going to show up as organic search traffic.
1:17:24So the only way to capture this is to ask people directly. Add a how did you hear about us question
1:17:30to your signup flow, your checkout process or your post purchase survey. include options like
1:17:36AI assistant, chat GPT, Perplexity, etc., and AI search like Google AI overviews.
1:17:43At Hrefs, around 3% of our conversions came from AI over the last year based on self-reported data.
1:17:50And our AI visitors convert at a much higher rate than organic search visitors. But we would never
1:17:56have known that without asking. So, if you only do one thing from this lesson, add that question
1:18:02to an entry survey. It's the most direct way to connect AI visibility to actual business results.
1:18:08Now, these three pillars work best when you use them together. Referral traffic tells you
1:18:13what AI is sending to your site. Bot analytics tell you what content AI is paying attention to.
1:18:20And self-attribution tells you what's actually driving revenue. No single source gives you
1:18:25the full picture, but together they give you a pretty clear view of how AI is interacting with
1:18:31your brand and where you should focus your efforts. And on top of these three pillars,
1:18:36you've still got brand radar tracking your AI visibility across platforms, which I showed you
1:18:40how to do back in module 2. So now that you've got your analytics set up, the big question is,
1:18:46is all of this actually worth it? What's the ROI of AEO? and what should you actually be doing on a
1:18:53weekly and monthly basis to keep growing your AI visibility? That's what we'll cover in the next
1:18:58and final lesson. I'll see you there. Hey, it's Ammo and welcome to the final lesson in HF's AI
1:19:04search course. Now, throughout this course, we've covered everything from how AI search works to how
1:19:10to find the right keywords and prompts to creating and optimizing content, how you can earn mentions,
1:19:16and even how to set up your analytics for AEO. But there are three questions I haven't answered yet
1:19:22that are super critical to know. Is AEO actually worth it? How do you know if you're making
1:19:27progress? And what should you actually be doing on a regular basis to keep growing? So that's what
1:19:34this lesson is about. Let's get into it. So let's start with a big question. Is AEO actually worth
1:19:40your time? Now I'll be honest. If you look at raw traffic numbers, AI search is still relatively
1:19:46small. According to our data, AI referral traffic accounts for about 0.25% of a site's total traffic
1:19:53on average. And Google still sends about 210 times more traffic than the top AI platforms combined.
1:20:01So, if you're looking at this purely from a traffic standpoint, you might think it's not worth
1:20:05it. But here's where the story gets interesting. At Hrefs, our AI visitors convert at 23 times the
1:20:12rate of organic search visitors. And we're not alone. Verscell is seeing 10% conversion rates
1:20:18from AI traffic. Tally says AI is their largest acquisition channel and helped boost their ARR by
1:20:24a million dollars. Think about that for a second. The traffic volume is small, but the quality of
1:20:30traffic is significantly higher. And the reason for that is simple. When AI recommends you,
1:20:36it's already explained to the user why you're a good fit. So the traffic arrives prequalified.
1:20:43They're not browsing. They're ready to act. And on top of conversion quality, AI traffic is growing
1:20:50fast. It's grown about 9.7 times since last year. Chat GPT alone has grown 85% since January,
1:20:58it now sends more traffic than Reddit or LinkedIn. So, while the numbers are still relatively small
1:21:04today, the trajectory, it's pretty clear. AI traffic is only going to grow from here.
1:21:11But here's what I think a lot of people miss about AEO. The real value isn't just the
1:21:16clickable traffic. It's the brand awareness that happens inside the AI conversation. Every time AI
1:21:22recommends your product or mentions your brand, that's an impression you never had before. And
1:21:28most of those impressions never result in a click to your site. They result in someone googling your
1:21:33brand name later or engaging with your brand on social media when they see it in their feed
1:21:38because they recognize it. So, the way I think about it is this. AEO isn't an alternative to SEO.
1:21:45It's a new layer on top of it. And the brands that build that layer now, while it's still early,
1:21:51are going to have a massive advantage as AI search continues to grow. Now, the main downside,
1:21:56which we talked about in the last lesson, is that it's not perfectly measurable.
1:22:01But just because you can't measure something precisely, it doesn't mean it's not working.
1:22:06It's kind of like brand marketing. You can't track every billboard to a sale,
1:22:10but you know it shapes how people think about you. AEO is the same way. So, how do you know if you're
1:22:16making progress? Well, if you followed along in module 2, you set up your brand radar baseline
1:22:21and did your first brand gap analysis. Now, it's time to go back and check how things have changed.
1:22:27Pull up your brand radar dashboard and look at four key things. First, AI share of voice.
1:22:33How have you moved relative to your competitors? If your share has grown, your efforts are working.
1:22:39If it stayed flat while a competitor has grown, you need to dig into why. At HFS, we're tracking
1:22:45queries and prompts at scale. So, brand radar, it gives you a really good look at the overall trend.
1:22:52Second, look at cited domains. Are new domains citing you that weren't before? This tells you
1:22:58if your mention earning efforts from module 3 are paying off. Third, topic coverage. Have you closed
1:23:04the gaps you identified? Are there new topics where you're showing up where you weren't before?
1:23:10And fourth, mention sentiment. Is AI saying accurate and positive things about your brand?
1:23:16This is especially important because AI doesn't just repeat what you put on your site.
1:23:21It synthesizes information from everywhere. I'd recommend doing this as a quick monthly check and
1:23:27do a deeper competitive audit quarterly. Now, while we're on the topic of what AI says about
1:23:32you, there's something important that you need to be aware of. AI is vulnerable to misinformation.
1:23:38And I don't mean it in a theoretical way. We actually tested it. We created a completely fake
1:23:44luxury brand, planted three contradicting sources about it across a blog, Reddit, and Medium, and
1:23:50then asked eight different AI platforms about the brand. The results were pretty alarming. After the
1:23:56fake sources were planted, Gemini and Perplexity repeated the misinformation in 37 to 39% of their
1:24:02answers. They cited fake founders, fake cities, fake pricing stories, all presented as verified
1:24:09facts. Now, the good news is that Chat GPT was much more robust. It stayed under 7% and cited
1:24:15the brand's official FAQ in 84% of its answers. But the point is that not all AI platforms are
1:24:22equally resistant to bad information. So, what does this mean for you? It means you need to fill
1:24:27every information gap about your brand with specific and official content. Create an FAQ
1:24:34that directly addresses common questions. Use specific numbers and dates and facts,
1:24:39not just vague claims. Because when AI has to choose between vague truth and specific fiction,
1:24:46it tends to choose the specific fiction. Also, monitor what AI is saying about you regularly.
1:24:52If you spot inaccurate information, the fastest fix is to publish content on your own site that
1:24:57directly contradicts it and then work on getting the third-party source corrected. All right,
1:25:02so let's bring this all together with your AEO action plan. If you're wondering what to do first,
1:25:08here's what I'd focus on this week. Check your robots.txt for AI bot access. This takes about
1:25:145 minutes max, and it's the most common technical blocker. Make sure AI can crawl your site. Next,
1:25:21set up your AI analytics. Create the AI traffic channel in G4 or set up HF's web analytics. Add a
1:25:28how did you hear about us question to your signup or checkout flow. Start measuring from day one so
1:25:33you can see how you progress over time. Next, update your most important pages for freshness.
1:25:39Remember, AI content is 25.7% fresher than what ranks in traditional search. Pick your top five
1:25:46to 10 pages and make meaningful updates, new stats, updated examples, current information.
1:25:53Next up, run your brand gap analysis. Set up brand radar if you haven't already, and
1:25:58go through the process we covered in module two. Know where you stand before you start optimizing.
1:26:05And finally, identify your top 10 mention earning targets. Use the cited domains and pages reports
1:26:11in content explorer to find the pages where getting a mention would have the biggest impact
1:26:16on your AI visibility. And then on an ongoing basis, do a monthly brand radar check to track
1:26:22your progress in a quarterly competitive audit to catch bigger shifts and just rinse and repeat.
1:26:28Everything I just mentioned is covered step by step in this course. So if you need a refresher
1:26:33on any of it, just go back to the relevant lesson and then execute. AI SEO or AEO is still early.
1:26:40The tools are evolving, the data is getting better, and the opportunity is only going to grow.
1:26:46So the biggest advantage you can have right now is simply starting before everyone else does.
1:26:52Thanks for watching our AEO course and I'll see you in the next

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