What six months of measuring my own AEO visibility actually showed
I tracked my own AEO visibility for six months. FAQ schema and verbatim question matching didn't move it, and the reason isn't the content.
People - the True Heart of Decent Marketing
My talk at The Marketing Meetup's Cambridge chapter argued that AI visibility is a brand problem, not a content problem, backed by 5,095 real citation checks showing two published articles that never moved a single query they were written for.
Most B2B marketing revenue doesn't come from discovery. It comes from people who already know you.
Most early-stage B2B revenue traces back to people you already knew, not to search or campaigns. Relationship-mediated buying is the main mechanism, and marketing strategy should be built around it.
Testing whether I should reuse old content
I fit a hierarchical Bayesian model to test whether retitling old content for AI citation works, and a robustness check collapsed the one clean result it found.
My AI visibility went from zero to 26% in six weeks. The one category still at zero is the one this post is about.
Six weeks after publishing a zero-appearance rate across every AI platform, most categories moved. The one still at zero is AI Search Visibility itself.
I am invisible on every AI platform. Here is the data.
For ten weeks I ran an AI visibility measurement system across ChatGPT, Gemini, Copilot, and Perplexity. My appearance rate for non-branded queries is zero. Here is what the data actually shows.
There Are Two Kinds of AI Memory
New bjrees.com tracking data shows branded AI visibility holding steady for months while topical visibility decays in 6-7 weeks - confirming the AEO decay-curve hypothesis with real numbers.
B2B Marketing Measurement*
An updated marketing measurement framework, now with a layer for AEO and GEO performance built in.
Brand is how you impact GEO
Brand impact has always been hard to measure. Generative engines, which have to synthesise a point of view, finally make it visible.
Making decisions in a Bayesian world
Most marketing decisions can't be A/B tested. Bayesian logic, combining prior knowledge with whatever data you do have, fills the gap.
The marketing flywheel - an alternative to the marketing funnel
Why ROI calculators aren't enough
How We Grew Marketing Sourced Pipeline by 20% in One Quarter
Why judging marketing by what happened this quarter is the wrong lens, and how Redgate grew marketing-sourced pipeline 20% anyway.
How Collaboration Can Grow Revenue
Five Myths About The Marketing Revenue Engine
Five widely-held beliefs about measuring marketing performance that didn't survive contact with the real world at Redgate.