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Found in AI: AI Search Visibility, SEO, & GEO

Found in AI: AI Search Visibility, SEO, & GEO

著者： Cassie Clark
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Found in AI is a podcast for marketers, founders, and content strategists who want to understand—and win—AI search visibility in the new era of search.


Hosted by Cassie Clark, fractional content strategist and AI search visibility consultant for startups and enterprise brands, the show explores how platforms like ChatGPT, Perplexity, Gemini, and Google’s AI-powered search experiences discover, select, and surface content.


Each episode breaks down real-world experiments, SEO, GEO / AEO, and content marketing strategies designed to help brands get found in AI-generated answers, not just traditional search results.


You’ll learn how to:


-Optimize content for AI-driven search and answer engines

-Blend traditional SEO with AI search optimization

-Build entity authority across search, social, and AI platforms

-Drive traffic, leads, and trust as search behavior continues to evolve


If you’re trying to future-proof your content strategy and understand how AI is reshaping discovery, Found in AI gives you the frameworks, insights, and tactics to stay visible—wherever search happens next.

© 2026 Found in AI: AI Search Visibility, SEO, & GEO マーケティング マーケティング・セールス 経済学
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  • Microsoft Clarity's New AI Citation Filter, LinkedIn's B2B Guide, and Claude Has a New Watermark

    Microsoft Clarity's New AI Citation Filter, LinkedIn's B2B Guide, and Claude Has a New Watermark
    2026/08/13

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    📬 You like this podcast? You’ll love the newsletter.
    Join the weekly The Visibility Report: subscribe

    A few stories with real strategic implications, and one that's generating more heat than light this week.

    First: Microsoft Clarity adds branded vs. non-branded query segmentation to its AI Citations dashboard. Cassie breaks down what the new filtering actually shows you, why separating brand-led demand from category discovery changes how you interpret your citation data, and what Share of Authority looks like when you can finally split it by query type.

    Then: LinkedIn publishes its first comprehensive B2B AI search guide, backed by internal data and eighteen months of their own testing. Cassie pulls out what's actually useful, including why LinkedIn is the number one most-cited domain for professional queries in AI search, how articles and posts do different jobs in the citation ecosystem, and the org alignment point that most brands are still missing.

    Plus: Sundar Pichai announced Gemini hit one billion monthly users, Shopify's Q2 data shows AI-referred sessions growing 197% year-over-year with double the conversion rate in research-heavy categories, and the Claude watermarking story — what we actually know, what's still speculation, and why you shouldn't change your workflow yet.

    In this episode:

    • What branded vs. non-branded grounding query segmentation actually tells you
    • How to use Share of Authority data now that you can filter by query type
    • Why LinkedIn articles and posts do different jobs in AI search
    • The org alignment problem LinkedIn's own guide surfaces
    • What Profound's citation timing data means for how you evaluate new content
    • What Gemini's milestone signals about where AI search is headed
    • What Shopify's Q2 data says about buyer behavior in research-heavy categories
    • What we actually know about Claude's watermarks — and what's still noise

    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 cassie@cassieclarkmarketing.com.

    Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

    Let’s connect:

    LinkedIn → Cassie Clark | AI Search Visibility Consultant
    Website → https://cassieclarkmarketing.com
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    10 分
  • Start Here: The 5-Step AI Search Visibility Strategy from 80+ Episodes

    Start Here: The 5-Step AI Search Visibility Strategy from 80+ Episodes
    2026/08/11
    Send us Fan MailIt's the official one-year anniversary of Found in AI! In this solo episode, I go back through the entire Found in AI archive and pull out the five-step strategy for AI search visibility — built from a year of guest conversations, prompt tests, and a few things I got wrong along the way.Whether you've been listening since episode one or you just found the show, this is your starting point.What's covered:Why AI search visibility is a cross-functional problem that shows up looking like a content problemThe five-step strategy: Describe → Structure → Refresh → Corroborate → MeasureHow the FSA Framework (Freshness, Structure, Authority) fits into a broader visibility strategyWhy fixing your brand description across surfaces is step one — before you touch your contentThe weekly assignment you can do in an afternoon to find your actual roadmapEpisodes mentioned:Step 1 — DescriptionIs Your AI Visibility Problem Actually a Messaging Problem? — with David KirkdofferHow Does Local SEO Translate to AI Search Visibility? — with Tommy LandryStep 2 — Structure (FSA)How Do AI Engines Decide What to Cite? The FSA Framework ExplainedStop Optimizing Keywords for ChatGPT — with Shane TepperWhat AI Engines Actually Want (And Why Your Blog Posts Aren't It) — with Bryan McAnultyStep 3 — Freshness (FSA)How Approval Layers Slow Down AI Search Visibility — with Rose Ann MulletWhy Aren't AI Engines Citing Your Content? (Hint: You're Missing Knowledge Graph Enrichment) — with Paul RoweStep 4 — Authority (FSA)What Does It Take To Actually Get Cited in AI Search? — with Jonathan BentzThe 24-Hour Reddit Citation — with Carl PetersonSEO and PR Are Finally Married (And AI Search Is Why) — with Basha ColemanStep 5 — MeasurementWhat Do Bing's AI Performance and ChatGPT Ads Mean for Search?What is an AI Visibility Audit? (And Do You Need One?)AI Competitive Intelligence: How to Track What's Citing Your Competitors — with Vlad PivnevIf you're new here:New to AI search:What's the Difference Between SEO, AEO, and GEO?How Do AI Engines Decide What to Cite? The FSA Framework ExplainedShould You Skip SEO and Go Straight to AI Search? [2026 UPDATE]Trying to measure it:What is an AI Visibility Audit?How Should Brands Measure Visibility in AI Search?What Do Bing's AI Performance and ChatGPT Ads Mean for Search?Selling this internally:Is Your AI Visibility Problem Actually a Messaging Problem? — with David KirkdofferHow Approval Layers Slow Down AI Search Visibility — with Rose Ann MulletYou Can't SEO Your Way Into AI Search VisibilityWant the arguments:SEO Agencies Have 2 Years Left — with Gilad Pichar"Good SEO is Good GEO." But Is That True?AJ Ghergich / Botify three-part series (Parts 1–3)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 cassie@cassieclarkmarketing.com. Or request your AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/Let’s connect:LinkedIn → Cassie Clark | AI Search Visibility ConsultantWebsite → https://cassieclarkmarketing.com
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    27 分
  • Microsoft Clarity's AI Visibility Metrics and Google's Reddit Denial

    Microsoft Clarity's AI Visibility Metrics and Google's Reddit Denial
    2026/08/06

    Send us Fan Mail

    📬 You like this podcast? You’ll love the newsletter.
    Join the weekly The Visibility Report: subscribe

    Two stories in a slow week. First, Microsoft launched its first Advertising product newsletter and used it to announce that Microsoft Clarity's AI visibility suite now reports citations, citation share, grounding queries, and share of authority — a platform-defined, free metric for how often AI systems pick your domain over everyone else's.

    Cassie breaks down what's actually in the dashboard, why it matters that Microsoft framed this as bringing "the same rigor and transparency of reporting" to the AI era, and the org problem hiding in plain sight: this entity data landed in a paid media newsletter, with paid media recommendations attached.

    Then: Google told The Verge that Reddit gets no special preference in its ranking systems or AI search features — while Reddit absorbs a core update, a spam update, and a wave of people gaming it for AI placement. Cassie makes the case for why concentration risk on any single third-party surface is the real story there.

    Plus a note on why newsletter content is worth more than it used to be, and what Microsoft publishing this on LinkedIn might be doing.

    In this episode:

    • What Microsoft Clarity's four AI visibility metrics actually measure
    • Why "share of authority" being platform-defined matters
    • The question to ask your team this week about Clarity
    • How to treat Microsoft's conversion stats before you put them in a deck
    • What Clarity shows you — and the layer it doesn't
    • Why a newsletter with a public archive is a retrieval surface, not just a list
    • The gap in Google's Reddit denial
    • Third-party mention concentration and why it's a risk

    Resources:

    Microsoft's Product Newsletter August 4, 2026

    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 cassie@cassieclarkmarketing.com.

    Or request your 7-Day AI Search Visibility Audit: https://cassieclarkmarketing.com/ai-search-visibility-audit/

    Let’s connect:

    LinkedIn → Cassie Clark | AI Search Visibility Consultant
    Website → https://cassieclarkmarketing.com
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    15 分
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