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This episode has a slide deck that we speak to that you can view on Youtube.  Most brands are approaching AI search like SEO: track a few prompts, check if you show up, count citations. But AI search has a fundamental difference from SEO: LLMs know far more about the user than Google ever did and they use that information to delivery extremely personalized recommendations to the user. Google got short keywords from users, and gave everyone more or less the same list of links to read for a given keyword. In SEO, the user did the research and decided which solution was right for their situation. LLMs, in contrast, have a massive amount of conversation history full of rich nuance about the user and their pain points. They then use this information and do research on behalf of the user and deliver personalized solutions for them and their specific pain points. Succeeding in this personalized AI search world requires teaching LLMs every scenario where your product or service could be a good solution, then getting that content discovered when they search the web. This talk shares the real customer chats and data behind this argument and walks through how to build this strategy for your own brand. - Why prompt tracking and citation counting mislead you: how LLM memory and user context create Invisible Prompts that no tool can see- How LLMs actually choose what to recommend: matching everything they know about the user against everything they know about your brand- How to publish content that teaches LLMs when and why you're the right fit, and get it discovered, with data from 100+ clients https://www.growandconvert.com/ai/personalized-geo/

In this episode, we break down how we think about reporting on AI visibility, why we built Traqer around topic-level tracking instead of individual prompts, and what we actually do with the data once we have it. We walk through a real client example in the call center software space to show how this works in practice. We cover why prompt volume data isn't what people think it is, why you can't bring an SEO mindset to AI tracking, why averaging across LLMs produces nonsense numbers, and how to turn visibility data into an actual action plan of what content to create and where to get mentioned. The lessons apply regardless of which visibility tool you use.

We joined Alex Birkett from Omniscient Digital for a wide-ranging conversation on GEO strategy, the state of the AEO conversation online, and how AI search is changing content marketing at a fundamental level. This one covers a lot of ground. We get into why we think most of the GEO advice circulating on LinkedIn right now is either misleading or just wrong, from the "Reddit is the most cited source" narrative to the newsletter sponsorship pitch to the ClickUp study that keeps getting cited as proof that listicles are dead. We walk through our own citation data across 100+ prompts and explain why what we're seeing on real client accounts looks nothing like what the aggregated studies suggest. From there, we get into the bigger strategic picture: how AI search is personalized in a way Google never was, why that changes the content you need to create, and why this is a strategy problem that nobody's treating as one. We revisit the Nicole story, talk about why Pain Point SEO needs to evolve for AI, and dig into why the "just get mentions everywhere" approach to third-party outreach is a short-sighted play. We also get honest about something we've been thinking about a lot internally: the long-form written content that built our agency may not work the same way anymore. People aren't binge-reading blog posts like they used to. LLMs are summarizing your arguments into two lines. So where does thought leadership actually live now?

AI search doesn't work like Google and your content strategy probably hasn't caught up. When someone searches Google, they type a broad keyword and filter through the results themselves. When someone searches ChatGPT or Claude, the LLM already knows who they are, what their business looks like, and what problems they're trying to solve. It's not returning a list of options. It's making a recommendation. That changes how you need to approach what content to create. In this episode, we break down why GEO is fundamentally a strategy shift, not a set of on-page tactics. We walk through a real client example where ChatGPT recommended us as the #1 agency for a prospect, but when we tried to reproduce that result in an incognito window, we didn't appear at all. Same prompt structure, different user context, completely different output. AI search is personalized. The LLM is running a matching algorithm between the user's specific situation and whatever it can find about your brand. If your content only speaks in broad category terms, you're invisible to the people who are your best customers. We cover what this means for content strategy, why most of what people are calling "GEO/AEO tactics" misses the point, and how we're shifting our own client work to account for this.

Most GEO/AEO advice assumes you're already a known brand. Here's how we'd approach GEO/AEO if you're not. Redline Capital is a business funding company that came to us after running mostly outbound. They didn't really have an online presence, no SEO foundation, and they were competing against incumbents that had invested in SEO for years. In this solo episode, Devesh walks through their Traqer dashboard and shows exactly how they went from roughly zero AI visibility to ~30% across ChatGPT, Perplexity, Gemini, AI Overviews, and AI Mode- and which parts are still at zero, and why that's fine. Covered in this episode: → Why new brands can't get into an LLM's training data — and why web search is your only realistic wedge in → The Prioritized GEO pyramid, and why owned content beats off-site mentions when you're starting from nothing → Why a single blended "AI visibility %" is misleading and trivially gameable — drop the topics you lose and the number goes up → Why prompt tracking is not keyword research, what clickstream data actually is, and why it misses your B2B buyer entirely → The self-promotion myth, busted: Redline's own product page is the #1 citation and a named brand mention in ChatGPT, ranked above NerdWallet, Wall Street Journal, and Forbes → Citations ≠ brand mentions — and why getting cited ninth is worth almost nothing → Why attribution gets harder as you win: when LLMs name your brand without linking, people just Google you, and it lands as direct traffic Prioritized GEOInvisible Prompts Topic-Based GEO Pain Point SEO Traqer (our AI visibility tool) Questions about your own brand? Drop them in the comments, we read all of them. Newsletter

Most GEO advice is wrong. Everyone's recommending llms.txt files, FAQ schemas, and content tweaks, but none of that actually influences whether ChatGPT, Claude, or Gemini recommend your brand. In this webinar, Devesh Khanal (co-founder of Grow & Convert) breaks down what actually drives visibility in AI search. You'll learn:- Why most AI traffic is "dark traffic" you can't measure in analytics- The flawed advice everyone's following (and why it won't move the needle)- About our GEO prioritization pyramid that we use to get real visibility for clients (and why tier 1 content matters most)- How to stop thinking in keywords and start thinking in topics- How to measure AI visibility without clean attribution If you're doing GEO or trying to be visible in ChatGPT, Claude, and other LLMs, this framework flips the script on what most people are doing. Related content:Topic Based GEOPrioritized GEO Learn more:📧 Join our newsletter: growandconvert.com🔧 Try Traqer.ai (7-day free trial): traqer.ai💼 Work with us: growandconvert.com

"Third-party content drives 85% of brand discovery in LLMs." It's the GEO stat making the rounds on LinkedIn right now, and a lot of marketers are using it to argue that your own site content doesn't matter anymore- that GEO is really about getting mentioned everywhere else. We disagree. And we have client data that contradicts it. In this episode, Devesh and Benji break down where this narrative came from (an Air Ops post citing a Graphite study), where the methodology breaks down, and what we're actually seeing across our clients in Traqer.ai.  The short version: big brands like Salesforce and Peloton skew studies like this because they already have category-level brand awareness.  For smaller players like Toro TMS and Climb Hire, clients we've worked with where their own content is essentially all we've done, they're pulling strong brand mentions across ChatGPT, Perplexity, AI Overviews, AI Mode, and Gemini. That's not third-party publications doing the work. We also get into:– Why Perplexity, AI Overviews, and AI Mode behave differently than ChatGPT and Gemini (and what visibility numbers look like across each)– The growing evidence that LLMs may decide what to recommend from training data and a loose SERP read first, then find sources to cite after the fact– Why competitive categories (CRM, exercise bikes, content marketing agencies) need a different playbook than less-saturated ones– Why your own site is the only place with enough canvas to spell out the specific use cases, pain points, and customer types that LLMs match against real user conversations Referenced posts: Invisible Prompts and Topic-Based GEOhttps://www.growandconvert.com/ai/invisible-prompts/https://www.growandconvert.com/ai/topic-based-geo/ This is the companion to last week's episode on self-promotional listicles for SEO. Watch that one first if you haven't. Subscribe for new episodes. Newsletter and full written breakdowns: growandconvert.com/newsletter #GEO #AISearch #ContentMarketing

"Self-promotional listicles are dying" is the new SEO narrative making the rounds and we've had multiple clients Slack us asking if we should change our strategy of producing list posts. In this episode, we break down Lily Ray's Substack post that started it all, walk through why the data she shared shows correlation but not causation, and pull up the actual rankings of category-keyword listicles we run for clients to show what's really happening after the late-January 2026 traffic dip. Then we get into the part nobody else is talking about: - How to actually write these posts so they hold up through core updates. -Why you don't need to force-rank a list. -Why you don't need to call yourself "the best." -Why the first-person "I tried all 15 of these" framing is a lie that backfires. -And why product schema hacks will get your site torched. We walk through a negative example, then show two posts that have ranked through multiple Google updates- our own "Best Content Marketing Agencies" post and a client example in trucking management software. The full written breakdown with screenshots and ranking data is going up on the blog — link in the newsletter: growandconvert.com/newsletter Full blog post on this topic: https://www.growandconvert.com/seo/self-promotional-listicles/

A client told us ChatGPT kept recommending Grow and Convert until she had to reach out. So we copied her exact prompt into an incognito window. We were nowhere to be found. That one example changed how we think about AI search strategy entirely. In this episode, we introduce Topic-Based GEO, our new framework for content strategy in the age of AI search.  We explain the concept of "invisible prompts" (the personalized context behind every AI search that makes prompt-level tracking unreliable), walk through how to build a topic map for your business, and share practical steps for creating the kind of content that actually gets LLMs to recommend you.

Most people optimizing for AI search are focused on the wrong metric. Getting cited by an AI model feels like a win but a citation doesn't mean you're actually influencing the answer.  And after sampling AI search prompts over 20,000 times, the data makes that painfully clear. In this episode, Devesh and Benji from Grow and Convert sit down with Bernard from Clearscope to break down what's really driving AI recommendations and what isn't.  They get into why Gemini searches an average of 5.7 times per query while ChatGPT barely searches at all, why Google appears to be actively suppressing brand citations even when it mentions you, and why the GEO "hacks" everyone's pushing right now (schema, Reddit, you name it) aren't moving the needle. The bigger takeaway: training data controls 70–80% of what AI recommends. Web search only affects 20–30%. Which means the content strategy that actually works in this new era isn't about producing more it's about going way more specific. In this episode: Why getting cited by AI ≠ influencing the answer Gemini vs. ChatGPT: how differently they search (and why it matters for your strategy) The brand suppression finding: why mentioning yourself might be hurting your citations Why "Content 2.0" is about persona-specific, long-tail content not volume How Grow and Convert is evolving Pain Point SEO for the AI search era Relevant articles:Invisible prompts: https://www.growandconvert.com/ai/invisible-prompts/Topic Based GEO: https://www.growandconvert.com/ai/topic-based-geo/

Your ChatGPT traffic is probably 5-10x higher than what your analytics shows. We used to think AI traffic was a small fraction of Google. We showed you the data a few episodes back — ChatGPT was about 3-4% of organic Google traffic across our clients. We've revised our thinking. In this episode, we break down why analytics tools are dramatically underreporting LLM-driven traffic and leads, why Google AI Overviews are creating the same attribution blind spot, and what you should actually be doing about it. The core issue: when someone discovers your brand in ChatGPT or a Google AI Overview, they don't click a trackable link. They open a new tab, Google your name, and land on your homepage. Your analytics says "direct" or "organic." The real source? An LLM. The only way to know? Ask them. We walk through real examples from our own data and client accounts, show exactly how this plays out in ChatGPT and Google AI Overviews, and share what we're changing in how we measure and report on content performance.

For the last 10-15 years, marketing has been dominated by the performance marketer - everything measurable, everything attributable. Creative marketers with big campaign ideas couldn't get the budget or the dev and design resources to bring them to life. AI is about to flip that. Now a single creative marketer can go from vision to finished product- building interactive tools, data-driven content pieces, mini apps, landing pages- without waiting on developers or designers.  The people with the best ideas (not just the biggest budgets) are about to win. In this episode, Devesh and Benji break down why this shift is happening, how Grow and Convert is using AI internally to maintain their quality bar while unlocking entirely new types of content projects, and why most agencies pumping out automated AI content are setting themselves up for failure. We also cover which AI predictions from 2023 actually came true, what Google's "shadow penalties" look like in practice when marketers try to automate content, and why producing written blog posts at a high level is about to become table stakes for good content teams. Read the article: https://www.growandconvert.com/ai/ai-creative-marketer/

Did you know that when you ask ChatGPT for a product recommendation, ChatGPT can recommend 50+ different brands for the same prompt? In this episode, we break down Rand Fishkin's latest research on the extreme variance in AI search results across ChatGPT, Claude, and Google AI Overviews.  His team gathered 600 volunteers, ran nearly 3,000 queries, and the findings are eye-opening. Here are some key insights: LLMs can share 50 different companies for each product related prompt.  The chance of getting the exact same list of brands twice is less than 1%. The top 6 brands are mentioned over 80% of the time.  So what does this mean for marketers trying to track their GEO (Generative Engine Optimization) performance? Most AI visibility tools give you a misleading snapshot — you ran one prompt, you showed up, and you think you're winning. But run it again and you might not show up at all. We walk through Rand's key charts and takeaways, explain why "rank" is meaningless in AI results (unlike SEO), and show how the top brands in any category still get mentioned consistently 70-90%+ of the time. Then we hop into Traqer.ai to show how our topic-based GEO approach — running multiple prompt variations per topic — gives you a far more accurate and responsible picture of your actual AI visibility. If you're doing GEO or reporting on AI visibility to leadership, this is a must-watch. 📖 Rand Fishkin's full blog post: https://sparktoro.com/blog/new-research-ais-are-highly-inconsistent-when-recommending-brands-or-products-marketers-should-take-care-when-tracking-ai-visibility/🔗 Our blog post on Topic Based GEO: https://www.growandconvert.com/ai/topic-based-geo/🔗 Check out Traqer: https://www.traqer.ai/

(Sorry about the audio quality on this one, it was recorded with the wrong microphone-- this episode is better viewed with screen share on Youtube) Most teams struggle with AI writing tools because they try to use them as a replacement for writers (and they use tools that don't understand the core arguments of what is trying to be said). In this video, Devesh walks through a real example of how he uses our AI writing tool Wave Writer at Grow & Convert to edit and restructure content. You’ll see how a rough outline and half-formed ideas can be turned into clear, on-brand draft copy, without losing the core ideas and without hallucinations. The video covers: How outlining arguments first leads to better AI output How to speed up the editing and content creation process using Wave Writer Why writing final prose is the slowest part of content workIf you’re responsible for editing content, managing writers, or shaping content strategy, this video shows a practical way to use AI that supports thinking instead of trying to replace it. Check out our product https://www.wavewriter.ai if you're interested in using an AI writing tool that understands your business, key arguments and helps speed up the writing process while keeping content quality high.

Most marketers track their AI visibility… but have no idea what to do next.This episode shows the exact GEO strategy to actually increase your mentions in ChatGPT and Perplexity. In this episode, we show you exactly how to implement GEO (Generative Engine Optimization) the strategy brands are using to increase their mentions inside LLM answers. You’ll learn: Why most AI rank trackers are inaccurate and how we rebuilt Tracker to scrape real results (not API hallucinations)How to turn visibility data into action — what content to publish, what topics to prioritize, and where your gaps really areThe GEO Pyramid and why 90% of marketers focus on the wrong tacticsHow to find the exact pages LLMs are citing — and how to influence them with targeted content and outreachWhy you MUST choose bottom-of-funnel topics if you want actual pipeline from AIA step-by-step walkthrough of improving visibility for a real company using owned content + targeted citation outreachIf you want a clear, repeatable strategy for ranking in ChatGPT, Perplexity, and Google AI Overviews, this episode breaks it down. 📩 Join the newsletter: growandconvert.com/newsletter🔧 Learn more about Tracker: https://www.traqer.aiGEO Pyramid article