AI Search is Personalized: How to Build a Content Strategy to Match
This episode has a slide deck that we speak to that you can view on Youtube (https://youtu.be/4rqHOzZBaH0).
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/
25 Sept 2026
How to Track AI Visibility as a Practitioner (Most people are doing it wrong)
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.
23 Sept 2026
Everything Wrong With the GEO Conversation Right Now - we join Alex Birkett of Omniscient Digital
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?
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