What I'm seeing in organic and AI search, and what I'd do about it.
Retrieval, citation, mention and recommendation are four different outcomes, and blending them into a single AI visibility score hides what actually changed. How to measure them separately and diagnose the gaps between them.
How to build an AI-search prompt set from observed buyer language rather than company vocabulary, and how to keep it stable enough for results to stay comparable over time.
How identical tools and AI workflows have made SEO intellectually conformist, and why mental models are the real competitive differentiator.
There is less than a 1-in-100 chance that ChatGPT or Google’s AI will produce the same list of brand recommendations if you run the same query 100 times. This is the starting point for understanding why AI search attribution is a fundamentally different problem from traditional search tracking.
A guide on turning customer language from Google Reviews into structured messaging for website copy using a specific message-mining framework.
A process to map out the internal linking structure of a website and apply statistical analysis to find stronger pages to link from, and those that have too few incoming links.
A study on the uptake of blocking OpenAI's GPTBot crawler across the top 1 million websites.
If you need someone to own organic and AI search at your SaaS or tech company, start a conversation.