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New data tracking over 1,000 business categories across 6 months of ChatGPT responses reveals something most CEOs haven't priced in: AI search category ownership is remarkably durable. Brands that establish a clear lead keep it 90% of the time, month over month. Brands with a narrow lead constantly lose it.

Jeff explains why the SEO metrics most companies have spent years optimizing — domain authority, organic traffic — barely predict who wins a category in AI search. He unpacks the divergence between being cited as a source and being mentioned as the answer, and why most companies are optimizing for the wrong one. Using a decade-long client relationship with a Portland periodontist as proof, Jeff lays out what it actually takes to build — and defend — durable category ownership in the AI era.

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Users almost never click the links inside an AI-generated answer -- roughly one in a hundred do, across every major platform. So if you’re grading AI search the way you graded a search ad, by the click that lands on your site, the scoreboard reads zero, every time, forever.

That's not proof that the channel doesn’t work. It’s proof you’re using the wrong scoreboard.

In this episode, Jeff makes the case that AI search doesn’t behave like a search ad -- it behaves like a billboard. And billboards were never measured by clicks. They were measured by proxies: awareness, recall, the slow creep of someone typing your name into a search bar weeks later. AI search is asking marketers to relearn a skill that performance marketing let them forget.

Jeff breaks down why traffic is the wrong lens, what to measure instead, and shares how one client is building an unmissable case across a standing Kiplinger byline, a #1 Amazon bestseller, a five-to-one video Masterclass, and a new wave of short-form video -- all without waiting for perfect attribution to prove it's working.

Three questions every CEO can start asking this week, and one free tool that catches the buyer who reads about you but never clicks anything.

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Most businesses have a proving department. It's just not on the org chart.

Every time someone on your team re-explains, re-convinces, or re-proves that your business can do what it says it can do — that’s not overhead. That’s a tax. And most business owners are paying it without ever putting it on a P&L line.

In this episode, Jeff introduces The Proving Tax — a companion framework to Proof Over Proximity — and breaks down the difference between proof that’s built once and proof that gets manufactured live, over and over, in every sales conversation. Featuring the story of how Provident 1031's Daniel Goodwin paid that tax exactly once, in writing, and has been collecting on it ever since.

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There are more qualified candidates, vendors, and consultants competing for every decision than there were five years ago — which means the people making the call can afford to be picky. Being competent gets you in the room. It's rarely what gets you chosen.

In this episode, Jeff introduces a new mental model — Decision Blur — the point where a decision-maker has evaluated enough qualified people that competence stops registering and distinctiveness becomes the only thing they can actually judge. But Jeff pushes back on the easy version of this idea: being memorable isn't automatically an advantage. It only works when it's backed by real, verifiable proof. Using a client story from his own photography business as proof, and drawing on a live situation from his own week, Jeff makes the case that the real advantage sits at the intersection of distinctiveness and trust — not one without the other.

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Everyone chasing AI visibility right now is chasing the same win: “We got cited.” A screenshot of a brand mention inside an AI Overview, posted and celebrated as proof that the strategy is working.

A new eye-tracking study says that win might mean two very different things — and most business owners can’t tell which one they just got.

In this episode, Jeff breaks down a finding buried in a new SERP eye-tracking study: that a single AI Overview, when the core generated answer is the core, converts 6 times better than a link cited underneath it. Same real estate, same "we got cited" moment — a massive gap in what it actually does for you. Jeff connects it to a real client transformation — from static PDF guides to an AI-embedded education platform — and lays out the one question every business should be asking about its own AI visibility right now.

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Instagram quietly rolled out a feature that shows users an AI-generated summary of what their content is "about" — and creators are finding it's sometimes wildly inaccurate. One marketer got tagged for "QR codes" in a post that never mentioned one.

That's not a glitch. It's a preview of how AI is already reading, categorizing, and deciding what every business is known for — on every platform, whether you're paying attention or not.

In this episode, Jeff connects Instagram's new AI-categorization feature and its upcoming Series (playlist) tool to the frameworks this show has been building around AI visibility: the Two Currencies of citations vs. mentions, and Proof Over Proximity. Using Daniel Goodwin of Provident 1031 — whose in-depth Masterclasses on the 1031 Exchange, Qualified Opportunity Zones, and Oil & Gas tax-smart strategies form a structured, authentic body of proof — Jeff makes the case that AI systems (and serious buyers) don't reward the loudest post. They reward the clearest pattern.

In this episode:

• Why Instagram's new AI-generated content summaries matter far beyond Instagram
• The uncomfortable truth: you don't get to write your own category anymore
• How Instagram's new Series feature rewards exactly the kind of structured depth that builds AI-recognizable authority
• Why Daniel Goodwin's Masterclass catalog is a blueprint for AI-legible expertise
• The one question to ask about your last twenty pieces of content

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Search your own business name right now — not your website, your name. Look at everything that shows up before anyone clicks: the outdated profile photo, the unanswered review, the AI summary at the top that might as well be describing your competitor.

Your website could be flawless. It wouldn't matter. You'd still be invisible where the decision actually gets made.

In this episode, Jeff introduces "digital availability" — the third lever of brand growth alongside mental and physical availability — and breaks down why breadth of credible presence across the web now matters more than a single polished page. Featuring a real proof point from a Portland periodontal practice that built search dominance through more than a hundred individual patient stories, not one perfect homepage.

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Could a competitor lift your last blog post, drop it on their own site, and nothing would look out of place? If so, it doesn't matter how many sessions it pulled or how many likes it got — it was never doing its job.

In this episode, Jeff breaks down why distinctiveness, not just visibility, is what turns content into brand equity. Drawing on research showing that AI-summarized search results push click-through rates under 1%, and a Nielsen Norman Group study finding 61% of users can't recall a brand from its own header logo, Jeff makes the case that most content today is commodity content — replaceable, forgettable, and building the category instead of the brand behind it.

He walks through the "steal test" for auditing existing content, the identity-layer checklist most teams never run (site name, Knowledge Graph entity, favicon, schema, OG images), and why a fully custom, interactive education platform built for a dental client is the kind of asset that can't be copy-pasted anywhere else.

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When's the last time you thought about your email inbox as a search ranking factor? Probably never — because it never was one. Until maybe now.

Researcher Garrett Sussman at iPullRank just ran a controlled experiment on Google's new "Personal Intelligence" feature, the opt-in setting that lets AI Mode read a user's Gmail and Photos to personalize search results. He seeded recommendation-style emails into a test account — some for real brands, some for brands he invented that don't exist anywhere on the internet. The invented brands got recommended anyway.

In this episode, Jeff breaks down what the study actually found: Gmail signals outperformed Photos by roughly 5x, seeded brands in the Personal Intelligence account jumped from a 24% to a 67% appearance rate, and even brands with zero web presence got surfaced in AI Mode recommendations a third of the time. Jeff connects this to his Two Currencies framework — mentions versus citations — and to a bigger open question the study raises but doesn't answer: does the presence of a quality email in someone's inbox matter, whether or not they ever open it? If so, the industry's obsession with open rates may be measuring the wrong thing entirely.

Three moves to take this week: stop grading your newsletter only on open and click rates, audit your customer emails the way you'd audit a landing page, and remember that citations still outrank mentions — personal context gets a brand noticed, but real web presence is still what makes AI systems vouch for it.

Source credit: This episode draws on original research by Garrett Sussman, published by iPullRank: "We Tested Google Personal Intelligence. Gmail Signals Changed AI Mode Brand Recommendations."

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44% of American adults now use ChatGPT — more than double the 2023 figure. At the same time, 63% say AI is advancing too quickly, and seventy-one percent think it's making their personal information less secure. Adoption and trust are moving in opposite directions, and most brands read that as a reason to pull back.

In this episode, Jeff breaks down why that's backward. New data from Pew Research, paired with analysis from Kevin Indig at Growth Memo, shows the trust gap is actually a brand opportunity: when users don't fully trust the machine, the named source inside the AI's answer carries the credibility the machine doesn't have.

Jeff connects this to his Two Currencies framework — mentions get you found, citations get you believed — and walks through how Burbank Dental Lab rebuilt static PDF guides into an interactive, AI-citable education platform that's already earned a confirmed, independently verified backlink.

Three moves to take this week: audit your top pages for citation-ready structure, track branded search lift after AI mentions, and put your differentiated point of view above the fold.

Source credit: This episode draws on Pew Research Center's "Americans and AI 2026" survey (June 17, 2026) and analysis from Kevin Indig's Growth Intelligence Brief, published by Growth Memo.