Why FAQ Schema is Your AI Search Secret Weapon

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In this episode of Found in AI, I sit down with Romana Kuts, founder of SaaStorm, to unpack how structured data and schema markup are becoming the simplest—and most overlooked—fix for AI visibility. We cover:

• Why short, direct FAQ schema is one of the strongest signals for AI engines.
• How author schema helps prove your content was written by a real human (and why that matters for trust).
• The difference between SEO schema vs. AI schema — and how crawlers read them differently.
• Whether you should bother with llms.txt — and what Romana’s A/B tests revealed.
• How to implement schema without turning your blog into an FAQ dump.

If you’ve been wondering how to adapt your SEO playbook for an AI-first search world — and which signals actually help you get cited in GPT and other LLMs — this episode is for you.

📌 Mentioned in this episode:

• FAQ schema and author schema
• llms.txt experiments
• AI visibility tracking infrastructure
• AirOps for AI-assisted content workflows

💬 Let’s connect:
 LinkedIn → Cassie Clark | Content Strategist
Website → cassieclarkmarketing.com

Keywords: Structured Data, FAQ Schema, Author Schema, AI Search Visibility, LLM Optimization, Generative Engine Optimization, B2B SaaS Marketing, AI Citations, Schema Markup, Digital Marketing

Find the show notes and transcript here.

Transcript

0:15

(Transcribed by TurboScribe.ai. Go Unlimited to remove this message.) Every founder wants their content to show up in AI Search, but most are missing the simplest fix, structured data. Welcome back to Found in AI, the show about getting your business discovered in AI Search. I'm your host, Cassie Clark, a fractional content strategist, founder of Cassie Clark Marketing, and currently CMO of ThoughtTree. Each week, I sit down with my neighbors camped out in internet land to talk about what's really working in AI visibility. In this episode, I'm joined by Ramana Kutt, founder of SassStorm, to unpack exactly how schema markup and those short, sweet FAQs can make your brand visible in AI engines. Here's part of that conversation. So I'm going to keep it kind of short because I've got feedback from listeners that they like the bite-sized episodes, so like 10, 15-ish minutes. But I've got a whole bunch of questions because I know we're talking about structured data. So first, tell me who you are, what you do, all the things. Yeah, of course. So my name is Ramana, and I'm founder of SassStorm. And SassStorm is a B2B SaaS marketing agency, and we position ourselves more as a revenue-focused B2B SaaS marketing agency because we really love to be in the CRM of our client, kind of track all the MQLs, SQLs, pipeline. So we're trying to be very much like data-driven. Of course, it's hard, but we're trying as much as we can sometimes. And basically, at SassStorm, our main strategies and services that we provide our clients with are actually content and SEO. And then, of course, complementary, depending on the client, we have some design and web development, some PPC support. But mostly, it's a very content, LLM optimization, and SEO optimization. So what have your clients been saying or asking about AI Search? That's a really good question. I think the first one is like, how can we see that chatGBT is doing citations and is quoting us? That's the first one, is like, how can we see? Are we visible in AI? And then the second question, when we answer that one, they're like, okay, how can we have more traffic from GBT? How can we be even more visible? So I think these are two of the most common themes and questions from our clients. And so your clients are already seeing results from changing up their strategy? Yeah, I would say so. Because first of all, you can always see if there's referral traffic coming from chatGBT. So very easy to track. And secondly, we set up the entire LLM tracking infrastructure for our clients. So we can see what prompts are there, how they are shown in different LLM models, what we can basically, how can we improve their visibility? So we are very much like, I will say the last three months, so basically Q3 was a big focus exactly on LLM visibility. And that's across the board. That's not just one or two, like trying to get in early. It's like everyone. Honestly, everyone. It's funny, like out of nowhere, it's like everyone was asking it. And I think me and my co-founder, just before Q3, we were like, yeah, we have to change something because they are starting asking more and more. So we just like proactively did it across all the clients. We didn't do any like extra charge or whatever. I just really feel that that's something that is like essential. So we just implemented a big like LLM optimization and LLM tracking project in Q3. So before we get into like the structured data topic, I want to ask you, because I was talking with someone else yesterday, everyone is either SEO is dead. No, it's not. GEO is silly. What's your thoughts on all that? Oh my God, like I'm following so many interesting people on LinkedIn. And every time I like every time I open it, I just see exactly the same conversations. SEO is not dead, you know, like as nothing is dead. Even cold calling is not dead. Like I think it's just like very nice to use this hook on LinkedIn and then like everyone's like, oh my God, what? So I really feel that all the LLM, GEO, etc. is just a good SEO. I still feel like it just really one of the types of SEO is just like doing something a bit different or exactly what we're talking today about more like using structured data, using schema markups and just optimizing all your like SEO content and SEO efforts just also for LLMs. Like I will say other process didn't change that much for LLM. Like if you were doing a good SEO, like you will also have a good LLM or GEO and any other O's a day. Like, I don't know. There are millions of terms to describe this. I've been calling it the alphabet. It's the whole alphabet. Yeah, for real. Like every day I see something different. I'm like AEO. I'm like, okay, answer engine optimization. There's like generative engine optimization and like learning models optimization. I'm just like, oh my God. Every day there's like a new abbreviation. I'm like, okay, let's choose one, please. Yeah, I think some people are trying to like be the person that coins it. But as of now, it's just the alphabet. Okay, so for listeners who just came up, how would you explain structured data in like plain English? Yeah, so I actually recently had to explain it to someone that had no idea how to explain it. So I was trying to break it down very, almost like for teenagers that just like trying to learn marketing. So I feel like when we read any content or any page on like on any website, we just read it normally. We just see a text. We see the heading. We see an image. But Google see it differently. Google sees that through the length, like a lens of code and snippets and basically different exactly schema. So for example, that's why schema is very important to implement because like humans don't see what is happening. But for Google, there are signals like, hey, guys, this is internal link. Hey, this is FAQ. You should use it as FAQ. Or like, hey, this is author schema, just so you know that this was written by a real human. So I think it just like the same as for humans, we just use letters the same way we use for Google, just like a certain like schema markup. Right. So what would be the difference between schema for SEO and like for the AI engines? Honestly, there's not a lot of difference here, I would say. So I think there are just like a few schema markups that are very important. And we were in some way, we were kind of ignoring them because Google is very much like traditional Google search was very much focused on keywords. So you could always win by having just the right keyword, et cetera. So we were sometimes ignoring, let's be honest, I'm sure that a lot of people will agree, we would not have FAQ schema markup, we would just add them this keyword. So it would be still, you could still find this content via Google, but for AI agents, so crawlers work differently because they don't just look at keywords, they are more like looking at conversations and they're looking for a certain like signals like, hey, this page is actually ready to be indexed by AI agent or being crawled. So that's why we started kind of focusing and talking about schema markup so much more because AI agents just like crawl information a bit differently. And I think because, so one of the most important ones and the one I recommend everyone to implement is actually FAQ schema markup just because it's 100% equals on how people are looking for certain things in chat GBT or perplexity or Gemini. You have like a long question and you expect like a nice answer. That's why that's like where FAQ schema markup comes into play because it's like, okay, cool, there's someone actually asking this question via covering this, like, hey, AI agent, please take information from here. So I think that's kind of the main difference. So that was gonna be my next question is which would be the most important one to add to the blog post. So changing the question just a smidgen because I work with a bunch of different clients across the board who are now starting to put in these FAQs. So have you noticed like a preference for how long the answer should be? Like which one works better, like a short answer, a couple paragraphs? And I'm asking for a specific reason because everyone's different. Yeah, yeah. So I honestly, even when I work with my content writers, I ask them to not do it more than like three sentences. I don't know, like 150 characters, probably 200 characters, not more for sure. So just like, I think very important in FAQ to not do this kind of intro, like, I don't know, someone's asking, like, what is knowledge management? Just answer, knowledge management is. Don't start it with like, if we are talking about knowledge management in 2025, there's definition to define, like all this stuff, like you just need to cut and just like very straightforward answer. I think that's what's the most important. And so, yeah, as I mentioned, like FAQ schema is like my favorite one. And I think very important is to not like overdo FAQs because sometimes I literally open a blog article and I can see that people added like 20 FAQs. I'm like, that's not a blog, that's not a blog article anymore. It's just like some kind of FAQ section. So I think you just need to be very like careful. I normally add three, five FAQs and each of them has like two, three sentences. Yeah, three to five is what I've been sticking with too. I have one client that was like, I want more than three sentences. Like I said, it's just been different across the board. Like when I think about, I think short and sweet, like here's your question, here's the answer. But I guess Jerry's still out on that one, I don't know. Yeah, yeah, I agree. And I think because like, you know, we are analyzing basically, so of course we can see that like there's traffic from GPT or perplexity. And I always try to analyze like, okay, we have this traffic, but like what exactly chat GPT is using for quoting you in like LLM. And many times, like for one of my clients, we implemented FAQ schema markup, started actively adding them. And I can see that most of traffic that is coming from GPT is coming from a very like short and sweet FAQ. So like answers, like when we literally just have like, yes, no, and just like a little explanation. So it's definitely working when it's like nice, short and sweet. Nice, short and sweet, yeah. Like the short sentences seem to be what they're picking up. So any other type of schema that you should start adding to your post other than just the FAQs? I would say author schema markup as well, because you know, now with all the AI, it's kind of like, it's obvious, it's so easy to write AI content. So I feel like adding author schema markup as well is amazing for AI agents is like, okay, hey, this was written by a real human. So, and also like with all the Google algorithms, like EEAT, when like expert content is very important, we started adding this schema markup still before all the like LLM trends and buzzwords. Only when like expert content was important, we started adding this. And I think it's very important. And so you add author schema markup and what we do for other clients, we try to have it very like short and also actionable. And like, as I said, nice, short and sweet, but like picture of the person, their real name, their LinkedIn profile, a short bio. So this way it's actually kind of, there is a real signal like, hey, it's actually the human behind. Because I see a lot of companies just have their blog and they will just have like no author or just like their company as an author. I think it's very important to have humans behind B2B content or any content. Yeah, which kind of brings us back to the episode that I released earlier in the week where we were talking about like digital PR and brand building. So you can have your name attached to something. I think that's gonna help both with branding and also like with the AI. So is that like an extra, like extra HTML code that you're adding to every post or is there something that you're using that just automatically puts it on there? We normally try to avoid as much of like extra manual work. So we just implement it across the entire CMS. We just ask of a developer to do it. So we like include this snippet and it's automatically added to every blog article. Some of my clients that are using other CMSs, they are sometimes doing it manually. But normally you can implement it on like a base code level and you have it across entire website. Across all of them. Yeah, that does make it a little bit easier. So do you think structured data will be even more important in an AI-first world or will LLMs get so good that just paraphrasing raw text where the schema will be less important? Look into your crystal ball and tell me what you think. Yeah, yeah. You know, like it's hard to predict but I personally really think that structured data will be more and more important. Even just from an angle of looking at like how important right now is becoming like AI engineering, AI content engineering. You know, that's like people are like big companies, they are hiring AI content engineers. And even from the word engineer, you understand that there's like a coding involved. Everyone is white coding different tools. Like I feel like literally yesterday, I was just like building a big automation workflow like in Python. And I'm just like, how did I end up here? Like how? Like I went to study journalism. I went into content marketing. Why am I coding right now? How the website should crawl the data? So looking at how the industry is developing, I actually think that it's going to be just more and more important. Yeah. I'm laughing because I literally had a conversation about two hours ago where we were talking about AI automation and like mapping out all the code. Neither one of us are AI engineers. Like we don't know what we're doing. We're just trying our best. Yeah, for real. I had like, I have two screens and I had this like my big advanced workflow open and I'm just like, something is taken from like cloud, something is taken from GPT, then it's like reverse engineer. And I'm just literally sitting and I'm like, I have no idea how I ended up here. It's just like so funny. But yeah, I think that's where my assumptions that like probably schema markups, codes in general programming, et cetera, will be only becoming more and more important in SEO and content. Right. So another question, like I know there's been talk all over LinkedIn about adding that LLMS.txt page to your website. Some people are like, no, don't do it. It's not doing anything. Everyone else is like, yes, you absolutely have to have that. What are your thoughts? But that's a very good one. I was expecting you will ask this one. So at the beginning, when all the LLM stuff started happening, I was like very much, even if you go and see my LinkedIn posts, I was like, yeah, add this one. You need it. It's helping. And we implemented it for some clients and for some we didn't. So we tried like to do a little A-B test and I haven't seen a difference, honestly. Okay. I just like personally, I haven't seen it. Maybe some people did. Maybe it depends on industry. Maybe it depends on competition. But in terms of growth, month over month or quarter over quarter growth in terms of LLM traffic, LLM citations, I cannot say that there was a difference between both. I just added it to my website like a couple of weeks ago. So I didn't see any difference either. But it could just be because I just did it a few weeks ago and it has to take time. I don't know. But that's interesting. Yeah. It's interesting. I actually want to explore this more again. Like I think we did it probably four months ago and then it was not working. But like I will probably revisit and it's actually interesting and maybe implement for other website. I kind of cannot recall even if you did it for other agency website. I will have to check it with my developer. Yeah. Yeah. Well, let me know what you find out on that. Because like I said, I just started a few weeks ago on that part. So I'm curious if you notice a difference after it being up for a couple of months. Yeah. Yeah. Definitely. Will do. Will do. Okay. So maybe my last like hard hitting question. If you are advising a resource strapped startup, so bootstrapped, what's the 80-20 of schema implementation that they should choose or focus on first? On a schema implementation, especially, right? Yeah. I would definitely go with FAQ schema markup. For real, I feel like everyone should have it. And there is like such an easy way right now to do it. So for example, like I am building right now an AI workflow that will automatically, for example, check the SERP and see all the competition and directly implement an FAQs for every blog article. So first of all, it's very easy to implement. Content writer can do it. You can do it like basically for every new blog article. But it's also very easy to revisit all the blogs that you have and just add FAQ schema. So I think that's my favorite one. And the second one would be definitely author schema markup. There's probably much more schemas, but like I normally add this too and they work really good for me, for our agency, for all of the clients. So I think that would be the balance. That's it for today's episode of Found in AI. Big thanks to Romana for breaking down how structured data actually drives visibility in AI search. I've been adding FAQs with most of my blog posts over the last month or so. And honestly, it's a pretty quick addition. So here's your experiment. Take one of your existing blog posts and add three short direct FAQs. With those answers, don't make them fluffy. Just make them as clear as possible. Then paste those questions and answers into chat GPT and ask it to generate the FAQ schema markup in HTML. Copy and paste that code directly into your CMS or ask your developer to do it if you have one of those. But with WordPress, it's super easy. There's an HTML block in the editor. Just click that block, drop in your code at the bottom of your blog post and publish it. So the viewer on your website, they're not going to see the code, but the AI crawlers will. So over the next few weeks, keep an eye on your analytics for AI-driven referral traffic or citations in chat GPT and make a note if they're going to those blog posts with the FAQ schema markup. Okay, quick ThoughtTree update. We are launching beta for ThoughtLab and ThoughtSpace, our AI workspaces that work the way that you think. If you'd like to test them out, and we would love for you to do that, we'd love your feedback too. So just head over to www.thoughttree.io to give it a whirl. I'd love to hear how your experiment goes this week too. Send me a note on LinkedIn if you're adding these to your blog post or you can find me at cassieclarkmarketing.com. And if you enjoyed today's episode, make sure to subscribe so you don't miss the next one. See you next week.