17 June 2025

How to Rank #1 in ChatGPT Results (AI SEO Strategy)

2Frameworks

10Insights

Frameworks in this episode

Strategy5 steps

AI Search Investment Decision Rule

Choose an AI-first or transition strategy based on existing organic traffic

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Marketing7 steps

Specificity-First AI Search Optimization Playbook

Build persona-specific content systems that earn visibility in AI answers

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Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Myth Buster· 2

Myth Buster18:30

Website Visits Are Losing Their Status as Marketing's Primary Metric

The speakers challenge the assumption that more visits reliably produce more customers. When research and nurturing occur inside an LLM, the website may receive fewer sessions even while the remaining sessions carry stronger buying intent.

Historical visit-to-customer relationships may no longer hold.
Many formerly measurable nurturing interactions now happen off-site.
Conversion-oriented visits become more important than total sessions.
AI visibility can supplement traffic as a leading metric.

“I think visits are fundamentally less important and in some ways in some ways unimportant.”
Kipp Bodnar · 19:00

“What we care about is that ultimate visit, that visit where they decide to become a user or a customer.”
Aja Frost · 20:00

#marketing metrics#website traffic#attribution#visibility

Myth Buster38:30

AI Citations Do Not Require a Top-20 Google Ranking

The episode highlights data showing ChatGPT citing many sources that rank outside Google's top 20 results. The proposed explanation is that highly specific pages can be useful for narrow conversational questions even when their domains lack traditional search authority.

Many cited sources sit outside Google's top 20.
AI systems may evaluate usefulness differently from PageRank-driven search.
Specificity can let newer sites enter AI answers quickly.
A new site may gain AI visibility before earning traditional rankings.

“these AI search assistants are referencing sites that are not in Google's top 20 results.”
Kieran Flanagan · 39:00

“I think it's all about specificity.”
Aja Frost · 40:00

#site authority#google rankings#chatgpt citations#long tail

Hot Take· 2

Hot Take10:30

AI Content Partnerships May Shape Which Sources Appear

The episode argues that licensing relationships and legal conflicts may affect which publishers an AI system uses. Reddit's frequent appearance is linked to partnerships with both Google and OpenAI, while litigation may discourage references to other publishers.

Personalization and publisher risk both shape the new search environment.
Source preferences can correspond with media partnerships.
Reddit and Quora benefit from large stores of user-generated content.
Legal disputes may influence source availability.

“If you map those preferences by the media and content sites that each LLM has partnered with, you can see clear relationships.”
Aja Frost · 12:00

“both Google and OpenAI have partnerships with Reddit and Reddit shows up very frequently for both.”
Aja Frost · 12:00

#publishers#licensing#reddit#copyright

Hot Take15:00

AI Search Has Reopened Marketing's Experimental Frontier

Aja Frost frames the disruption as an opportunity rather than only a loss of predictable traffic. Because established companies and startups are both learning the new rules, rapid experimentation can matter more than historical domain authority or team size.

Traditional SEO had become predictable but stale.
The new environment reduces incumbents' accumulated tactical advantage.
Fast learning creates an edge.
AI-powered systems let small teams participate.

“And now we have a brand new open field again.”
Aja Frost · 15:30

“The edge goes to the people who figure out the new tactics the most quickly.”
Aja Frost · 16:00

#experimentation#marketing innovation#startups#competitive advantage

Explainer· 3

Explainer03:30

Why an LLM Visitor Can Be Worth More Than a Search Visitor

Traditional organic visitors may arrive early in a buyer journey and require weeks or years of nurturing. An LLM can compress education, comparison, and solution discovery into one conversation, so users who finally visit a vendor may already be prepared to buy.

LLMs can conduct much of the buyer journey before a website visit.
AI referrals may be fewer but more commercially qualified.
Sales transcripts already contain buyers crediting ChatGPT recommendations.
The final conversion-oriented visit matters more than repeated educational visits.

“someone coming from an LLM is worth more to us than someone coming from traditional search.”
Aja Frost · 03:30

“Yeah, chatbt said you were the best, so I came to you.”
Aja Frost · 07:00

#buyer journey#conversion#llm traffic#b2b

Explainer08:00

Why Third-Party Sites Dominate AI Citations

A cited study found brand websites appearing in only a small fraction of AI-answer links, with aggregators and community sites receiving more exposure. The speakers propose two possible mechanisms: AI systems may view third parties as less biased, or their content may simply be easier to ingest.

Brand-owned websites were reportedly cited only 9% of the time in the discussed study.
Third-party formatting may align with emerging AI-search preferences.
Perceived neutrality may influence source selection.
Vendor sites can respond by making their content more ingestible.

“the brand brand's actual website was only mentioned 9% of the time.”
Kieran Flanagan · 08:30

“I think what we don't know yet is whether LLMs prefer third-party websites because they consider them less biased than vendor websites or if they…”
Aja Frost · 09:00

#citations#third-party media#content structure#ai answers

Explainer25:30

SearchGPT, Gemini, AI Overviews, and AI Mode Are Different Surfaces

The discussion separates ChatGPT's web-search system from ordinary model responses and distinguishes Google's Gemini app, AI Overviews, and AI Mode. Although Gemini powers multiple Google experiences, tracking the Gemini app alone does not measure visibility in AI Overviews or AI Mode.

SearchGPT is the search system used within ChatGPT.
ChatGPT can answer with or without actively searching the web.
Gemini tracking does not automatically include Google AI Overviews.
AI Mode is expected to become a central Google search experience.
Separate surfaces may require separate measurement tools.

“Search GBT is the searching system that chat GBT uses.”
Aja Frost · 25:30

“We use a separate tool to track AI overviews, which are those AI generated summaries at the top of a SER.”
Aja Frost · 26:00

#searchgpt#gemini#ai overviews#ai mode

Tool· 1

Tool21:00

What AI Visibility Tools Can—and Cannot—Measure

HubSpot uses Xfunnel to monitor visibility, citations, and share of voice across selected AI systems. The episode stresses that current tools use similar underlying approaches and cannot fully reproduce personal memory, conversational context, or actual query volume.

Share of voice is becoming an AI-search brand metric.
HubSpot selected Xfunnel partly for its experimentation focus.
Current tools simulate users through configured personas.
Hand-selected queries define a useful but incomplete playing field.
User memory and true question volume remain major measurement gaps.

“There's no moat in this space at this moment.”
Aja Frost · 22:30

“It's a very crude solution, but Kieran, I think it it gets to what you're talking about.”
Aja Frost · 25:00

#xfunnel#measurement#share of voice#personas

Takeaway· 2

Takeaway04:00

Google Was an Answer Engine; LLMs Are Action Engines

The hosts distinguish search's historical role in supplying links and answers from AI's growing ability to help users research, decide, and act. This makes AI discovery more valuable to businesses while also changing what marketers must optimize for.

Blue links direct users toward answers on external sites.
AI systems can personalize research and move users toward an action.
The shift changes both content strategy and commercial value.
Executives can use the distinction to understand why AI search matters.

“Google and those 10 blue links that was an answer engine.”
Kipp Bodnar · 04:00

“That's an action engine.”
Kipp Bodnar · 04:30

#search evolution#action engines#executive communication

Takeaway45:30

Attribution Is the Hardest Near-Term AI Search Problem

The episode closes with optimism about AI search opportunities but warns that forecasting returns remains difficult. Companies must align around new performance signals even though they cannot yet observe the complete chain from an AI conversation to revenue.

AI interactions hide much of the traditional funnel.
Incomplete attribution complicates budgeting and forecasting.
Teams need new performance expectations and shared metrics.
Curious experimenters can still benefit before measurement is perfect.

“you have to change how you're measuring the performance, right?”
Kieran Flanagan · 46:00

“I think the thing that's going to be a struggle in the interim is the attribution measurement.”
Kieran Flanagan · 46:00

#attribution#forecasting#marketing operations#ai search