Advertise on podcast: Found in AI: AI Search Visibility, SEO, & GEO

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search measurement is getting more sophisticated, but is the data becoming more reliable? In this week's Found in AI news update, Cassie Clark covers Bing's new Topics Portfolio beta, Ahrefs research showing shifts in ChatGPT citations toward primary sources, and Nozzle's findings about misleading Google results served to rank trackers. She also explores why missing ChatGPT referral tracking data could make AI-driven traffic harder to measure, plus Yahoo's latest AI search experiment. In this episode: Bing Topics Portfolio: What the new AI Performance beta reveals about topic-level citations, grounding queries, and content opportunities.ChatGPT citation trends: Why primary sources may be gaining ground and what the Ahrefs findings mean for brands publishing original content.Google SERP tracking concerns: What Nozzle found in 27.5 million search results pages and why marketers should validate sudden ranking changes.ChatGPT referral attribution: Why missing UTM parameters and referral data could make AI search traffic appear to decline even when visits are still happening.Yahoo's AI search tests: How follow-up questions are becoming part of the search experience.-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark talks with content marketer Ben Hale about what actually changes when you start creating content for AI search — and what doesn't. Cassie and Ben talk about how audience behavior should determine which AI engines you prioritize, why distribution is becoming an increasingly important part of content strategy, and how content needs to change when it moves from your website to platforms like Reddit. They also dig into the difference between AI mentions and citations, whether getting cited is actually enough to call your strategy successful, and how marketers can test new AI search tactics without chasing every new optimization trick that comes along. In this episode: Why you shouldn't treat AI search engines as a monolithHow to decide which AI engines actually matter to your audienceWhy third-party distribution belongs in your AI search strategyWhy copying brand content directly onto Reddit doesn't workHow to create product and comparison content that's actually usefulHow content structure can affect AI citationsWhy getting cited is only a leading indicator of successThe difference between AI mentions and citationsWhat still matters about writing for humansHow to design AI search experiments with clear timelines and success criteriaWhy marketers need to be willing to abandon tactics the data says aren't working-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search is moving beyond citations and recommendations. As consumers use AI to discover businesses (and personal agents begin browsing the web on their behalf), brands need to think about the entire information environment surrounding them. In this episode of Found in AI, Cassie Clark breaks down Google’s updated guidance on main content and fake authors, new data showing rapid growth in AI-powered local search, and Profound’s research into personal agents like Muse and Instinct. Together, these developments point to a larger shift: AI visibility is becoming less about optimizing for a single answer and more about whether humans and AI agents can discover, understand, verify, and act on information about your brand. In this episode: What Google’s new “good main content” guidance means for SEO and GEOWhy content structure matters without becoming another GEO hackWhy brands cannot manufacture authority with fake expertsHow AI is changing local business discoveryWhy AI recommendations still trigger additional verificationHow personal agents like Muse and Instinct browse the webWhat agent-driven discovery could mean for websites and marketersWhy AI visibility and agent readiness are becoming connected problems-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark talks with Peter Rota, an SEO professional with 15 years of experience, about the rapidly growing market for AI visibility tools — and where those platforms still have room to improve. Cassie and Peter discuss why actionability remains one of the biggest challenges with AI visibility software, what teams should look for when evaluating a platform, and why a visibility score alone may not tell you very much. They also dig into one of the biggest AI search measurement questions: should brands care more about being cited, mentioned, or actually recommended? Peter shares his own hierarchy — recommendation, mention, then citation — and explains why citations can sometimes come dangerously close to becoming a vanity metric if they aren't connected to meaningful business outcomes. In this episode: Where AI visibility tools are useful — and where they still fall shortWhy AI visibility data needs to lead to actionWhat to consider before paying for an expensive AI visibility platformWhy prompt-based visibility scores don't tell the whole storyWhy mentions and citations shouldn't be combined into one metricThe difference between being recommended, mentioned, and citedWhen citations risk becoming a vanity metricWhy the intent behind the prompt mattersHow to identify a perception gap between your website and an AI system's understanding of your brandWhy lower-funnel prompts may be more valuable to trackWhether your next AI search investment should be software or a person who can actually turn the data into strategy-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is expanding AI Mode’s monitoring capabilities, letting users have Google continuously watch the web for new information instead of repeatedly running the same search. In this episode of Found in AI, Cassie Clark looks at what persistent search could mean for content freshness and AI search visibility. Cassie also breaks down new research from Graphite analyzing nearly 500,000 AI shopping responses across ChatGPT and Google. While large and small retailers appeared at similar rates among cited sources, major retailers were significantly more likely to become the actual recommendation — another example of why citation presence and recommendation presence should not be treated as the same AI visibility metric. Plus, Google Search Console adds reporting for multimodal searches originating from tools including Google Lens and Circle to Search, and new research from Perplexity explores why retrieval systems may need more than the single passage containing an answer to provide enough context for a useful response. In this episode: Why Google AI Mode monitoring changes the traditional search journeyWhat persistent search means for content freshnessWhat Graphite found after analyzing nearly 500,000 AI shopping responsesWhy being cited by an AI system does not guarantee your brand will be recommendedHow prompt language can affect which retailers AI recommendsGoogle Search Console’s new multimodal search reportingWhy search intent increasingly exists without a traditional typed queryWhat Perplexity’s contextual embedding research tells us about AI retrievalWhy structuring content for AI shouldn’t mean removing useful context-- Found in AI covers AI search visibility, generative engine optimization (GEO), answer engine optimization (AEO), AI search measurement, and the changes marketers need to understand as platforms like ChatGPT, Google, and Perplexity reshape search and discovery. Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email her at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark welcomes back Tommy Landry, founder of Return On Now and author of The Signal and the Source, for a conversation about the connection between AI governance and AI search visibility. Internally, companies are connecting AI to CRMs, reporting systems, content workflows, sales data, and other sources of business information. Externally, AI systems are interpreting websites, third-party platforms, brand messaging, reviews, documents, and other signals to understand what a company is and what it does. And when those signals are incomplete, outdated, inconsistent, or just plain wrong, AI can still produce a very confident answer. Cassie and Tommy discuss why companies need human checkpoints around AI-powered workflows, who should be responsible for those checkpoints, and why AI governance can't simply be handed to one department. They also explore what this means for GEO and AI search visibility, including why brands need to think beyond citations and start paying closer attention to how they're actually represented inside AI-generated answers. In this episode: How internal AI governance connects to external AI visibilityWhat happens when AI is working with inaccurate or outdated company dataWhy inconsistent messaging across sales, marketing, and other departments can become an AI visibility problemWhere humans need to remain in the loopWho should be responsible for reviewing AI-generated outputsWhy AI governance requires subject matter expertiseHow automated content workflows can create brand and messaging problemsWhy AI search visibility is about more than tracking citationsWhat it means to measure your brand's AI representationWhy accurate positioning matters before a customer ever reaches your websiteHow third-party signals can shape what AI systems understand about your companyWhy AI governance is becoming a cross-functional business problemTommy also shares the thinking behind his new book, The Signal and the Source, and his framework for managing AI across both internal workflows and external visibility. Find it on Amazon. -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI is moving beyond answering questions and toward taking action on our behalf. But as agents handle more of the customer journey, what happens to the websites and publishers that make AI-powered discovery possible? In this episode of Found in AI, Cassie Clark breaks down two developments that reveal different sides of the future of search. First, Meta introduces Muse, a personal AI agent designed to complete tasks on a user’s behalf. Cassie explores what the shift from AI answers to AI actions could mean for brand discovery, the customer journey, and why being recommended by an AI engine may no longer be enough. Then, we turn to a story that deserves more attention: Yahoo Scout. Yahoo CEO Jim Lanzone is making the case for an AI search experience that keeps publisher links visible and preserves opportunities for referral traffic. Cassie examines why that approach matters, what it could mean for the economics of the open web, and why marketers need to look beyond citations when measuring AI visibility. In this episode:  What Meta’s Muse reveals about the shift from AI search to AI agents  Why brands need to think about agent readiness, not just AI visibility  How Yahoo Scout approaches AI-generated answers and publisher links  Why citations and referral traffic are not interchangeable  What the future of AI discovery could mean for marketers, publishers, and the open web Stories covered: Meta: Introducing Muse, a Personal AI Agent The Next Web: Yahoo Scout, Jim Lanzone, and the Future of Publisher Links -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Does ChatGPT recommend the same brands to everyone? In this episode of Found in AI, Cassie Clark talks with Joao from Friction AI about new research examining how personalization changes the brands recommended by ChatGPT, Gemini, Claude, and Perplexity. The study compared responses collected through APIs, anonymous AI accounts, and accounts that had been primed with specific user personas over two weeks. The results show that personalization does influence brand recommendations — but the effect varies considerably depending on the AI platform. Cassie and Joao discuss: How ChatGPT, Gemini, Claude, and Perplexity respond differently to personalizationWhat changed between API, anonymous, and personalized responsesWhy geography can affect the brands and sources AI systems surfaceWhat personalization means for local and global brandsWhy creating more content isn't automatically the answer when your brand isn't appearingWhat marketers should understand about the methodology behind AI visibility toolsWhy personalization doesn't make AI visibility measurement useless — it makes repeated measurement more importantRead the research: The original research report: The Personalization Gap: How a Model's Knowledge of the User Reshapes Brand Recommendations in Generative AI Cassie's insights Friction AI's insights -- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe OpenAI is testing a new kind of ChatGPT ad that doesn't just send users to a landing page. It starts a conversation. In this Found in AI news update, Cassie Clark breaks down OpenAI's new Sponsored Agents, Google's latest agentic commerce tools, and a new publisher licensing program that raises some interesting questions about how much Google can actually measure inside AI search. You'll learn: How OpenAI's Sponsored Agents could change the traditional ad-to-website journeyWhy ChatGPT ads point toward a much bigger shift in agent-mediated commerceHow Google is bringing Business Agents and more AI shopping capabilities into the customer journeyWhy Google's new AI share-of-voice reporting for retailers is worth watchingHow Google's pay-per-value publisher program complicates the conversation around AI search measurementWhy marketers need to think beyond AI visibility and start preparing for agent readiness-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this episode of Found in AI, Cassie Clark talks with Leah Nurik, CEO and co-founder of Brandi AI, about why brands need to think much more broadly about what influences their visibility in AI-generated answers. Cassie and Leah discuss why GEO is becoming a brand marketing and communications problem, not simply an extension of traditional SEO. They also dig into the role PR and earned media can play in establishing authority, why the sources that matter for AI visibility vary by industry, and why authentic storytelling may be more durable than trying to find shortcuts for influencing AI systems. They also talk about what makes a story compelling enough to earn media coverage, how brands can identify stories that actually add something new to their industry, and what may happen as AI-generated answers become a bigger part of the buyer journey. In this episode: Why Leah believes AI search represents a new buyer journeyWhy GEO extends beyond traditional SEO and your websiteHow PR and earned media can influence AI visibilityWhy authority signals differ from one industry to anotherThe role of peer reviews, user-generated content, and third-party coverageWhat makes a brand story interesting enough for journalists to coverWhy uniqueness matters for both PR and AI searchHow brands can build visibility that may be more resilient to model changesWhere AI search could be heading over the next five years-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe In this Found in AI news update, Cassie Clark breaks down Peec AI’s research into OpenAI’s Labrador retrieval index, including the separate indexes identified for web content, news, shopping, YouTube, PDFs, and more. Then, we look at Common Crawl’s analysis of more than 584,000 llms.txt files and what it tells us about the confusion surrounding llms.txt, robots.txt, and AI crawler access. Finally, Microsoft is preparing businesses for a future where AI agents don’t just help consumers discover products — they help choose and buy them. Microsoft’s latest agentic commerce guidance shows why structured, accurate, and current product data could become critical as AI moves from answering questions to taking action. In this episode: What Peec AI discovered about ChatGPT’s Labrador search indexWhy ranking in Bing isn’t a proxy for ChatGPT visibilityHow freshness appears within ChatGPT’s retrieval infrastructureOpenAI’s experiments with its own shopping indexWhat Common Crawl learned from 584,107 llms.txt filesThe difference between llms.txt and robots.txtWhy llms.txt does not control AI crawler accessMicrosoft’s recommendations for preparing for agentic commerceWhy structured product data matters when AI agents are shoppingThe difference between AI visibility and agent readinessWhy businesses should prepare for AI discovery even while the technology continues to changeSources Peec AI: “ChatGPT Built Its Own Search Index”Search Engine Journal: “Common Crawl Finds Widespread Confusion Around llms.txt & robots.txt”Microsoft Advertising: “How Businesses Win When AI Does the Shopping”-- Cassie Clark is an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Google is giving us a pretty clear look at what comes after AI search visibility: AI agents that don't just recommend brands, but help consumers take action. In this week's Found in AI news update, I'm looking at several recent Google developments that make much more sense when considered together. Google DeepMind says Gemini is evolving from a model into an agent. Meanwhile, Google is adding more of the customer journey directly into Search and AI Mode, including flight price tracking, hotel research and booking, product discovery, visualization, price comparison, and more. So, what happens when getting recommended by an AI engine is only step one? In this episode: Why Google DeepMind is thinking beyond the chatbotHow AI Mode is expanding from travel research into hotel bookingWhat Google's home decor features tell us about the changing buying journeyWhy AI search visibility is still critical, but may actually be the beginning of the journeyThe difference between being recommended by an AI engine and being ready for an AI agent to take actionWhy agentic commerce will require more than content and SEO teams alonePlus, I share why marketers should start asking a new question: Once an AI engine finds, understands, trusts, and recommends your brand, can an AI agent actually do something with it? Resources mentioned: Google DeepMind on Gemini's evolution from model to agent Google's new AI Mode travel and hotel booking capabilities Google's AI-powered Search features for home decor Programming note: Found in AI is taking a short Labor Day break, so there won't be a Tuesday episode next week. We'll be back with a new episode the following Thursday. I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Daniel Horowitz has spent more than a decade in SEO and now works as an enterprise SEO strategist at Salesforce, where he continues to lead AI search work for Informatica. One of the projects his team is testing challenges a pretty fundamental piece of the traditional B2B content funnel: gated content. Instead of locking valuable research, customer stories, and insights entirely inside PDFs, they're experimenting with a hybrid approach that makes the main ideas accessible as HTML while preserving the full gated asset for lead capture. Because if your best information is inaccessible to AI engines, they'll still answer your buyer's question. They may just answer it using someone else's information. In this episode: Why Daniel still considers SEO foundational to AI search — and where he thinks the two start to divergeWhy creating more content isn't necessarily the answer when valuable information is already buried inside your existing assetsHow Informatica is testing a hybrid gating strategy that makes the main ideas from PDFs accessible without completely abandoning lead captureWhat Daniel's team has seen so far from turning gated information into accessible, answer-first contentWhy strong point-of-view content can give AI engines something distinct to associate with your brandWhat "chunking" actually means — and why it doesn't mean chopping every article into tiny piecesWhy Daniel is experimenting with moving key takeaways from the bottom of articles to the topHow outdated website content can continue shaping what AI engines believe about your company, even when those pages aren't driving meaningful search trafficThe old Informatica product page that was reinforcing an outdated brand perception — and what happened after Daniel's team rewrote itWhy monitoring how AI engines characterize your brand can uncover a much bigger positioning or business problemWhat Daniel has learned about getting enterprise stakeholders and senior leadership on board with AI search initiativesI'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/ Wondering what AI search means for your business? Cassie Clark Marketing helps startups and enterprise brands understand how AI systems discover and recommend them, identify what affects their visibility, and develop executable strategies. Services include team training, AI visibility diagnosis, strategic consulting, and fractional marketing leadership. www.cassieclarkmarketing.com

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe AI search may have had a quieter news week, but several updates from Google and Yahoo point to a bigger shift in how people discover information online. Google is expanding personalization across Search and Discover, including new ways for users to choose the publishers they want to see more often. It's also bringing link carousels for developing topics into AI Mode, creating additional opportunities for publishers and brands to earn clicks from AI-generated answers. Meanwhile, Google's John Mueller says there's still “nothing really special” websites need to do for generative AI responses in Search. I explain why I largely agree with that advice when we're talking about Google, and why marketers shouldn't apply it to the entire AI search ecosystem. Plus, Yahoo is leaning into Yahoo Scout and its history as the original guide to the internet. Could AI give Yahoo another chance to become a meaningful discovery destination? In this episode: How Google's Preferred Sources feature changes the conversation around brand authorityWhy Google's new AI Mode link carousels matter for marketers and publishersWhat John Mueller's latest comments actually mean for GEO and AI search optimizationWhy Yahoo Scout is worth watching as AI search continues to fragmentWhat marketers should learn from Yahoo's broader push for users and relevanceA quick update on Google's August 2026 spam updateWhy brands need to become sources that both people and AI systems want to findMentioned in this episode: Google: New ways to personalize Search, Discover and Google News Search Engine Roundtable: Google Says Nothing Special Needed for Generative AI Search Responses Search Engine Roundtable: Google AI Mode Gets Link Carousels for Developing Topics Yahoo Scout I'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/

Send us Fan Mail 📬 You like this podcast? You’ll love the newsletter. Join the weekly The Visibility Report: subscribe Ryan Doser has been working in SEO for roughly a decade. But as search behavior has expanded beyond Google into ChatGPT, YouTube, TikTok, Reddit, and other platforms, he's started thinking about SEO differently: not just search engine optimization, but "search everywhere optimization." In this episode, Ryan and I talk about why long-form video can do much more than build a YouTube audience. It can give search engines and AI systems another surface for understanding who you are, what you know, and what your brand should be associated with. We also get into the growing importance of third-party trust signals, where traditional SEO still fits into AI search, and some of the GEO advice Ryan thinks marketers should be questioning. In this episode: Why Ryan thinks marketers should shift from "search engine optimization" to "search everywhere optimization"Why trust signals and third-party surfaces matter more as brands try to build visibility beyond traditional Google searchWhy Ryan has "never been more bullish" on YouTube as an AI search marketerHow YouTube can become the foundation for blog posts, newsletters, short-form video, and other contentWhere to start if your brand wants to build a YouTube presence, from defining your ICP to finding the topics they're actually searching forWhy Ryan recommends at least one long-form YouTube video a week — and why he favors evergreen content over constantly chasing trendsThe relationship between traditional SEO and AI search optimization, and why Ryan pushes back hard on claims that SEO is deadWhere llms.txt fits into Ryan's strategy — and why he considers it a small piece of a much bigger visibility puzzleWhy podcast appearances, media coverage, speaking, video, and other off-site signals can help establish what a person or brand is known forWhy starting your own podcast or another form of long-form content can create a foundation for visibility across multiple platformsI'm an AI search visibility consultant and a fractional content strategist for startups and enterprise brands. If that sounds like the kind of help you're looking for, email me at [email protected].  Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/ Join Cassie Clark for a free live training, How to Build an AI Search Visibility Strategy, on November 5, 2026, at 1 PM ET. Learn how to identify relevant AI search opportunities, diagnose visibility gaps, establish a measurement baseline, and prioritize your next steps. Includes live Q&A. Register for free: https://cassieclarkmarketing.com/ai-search-training/