Research and explainers
How AI models decide who to name, how to measure it, and what moves the number. 5 articles by C. Kerger, who runs the measurements.
What is AI visibility? A measurable definition
AI visibility is how often and how prominently an entity appears unaided in AI model answers. Here is a definition you can actually measure — and how it relates to GEO and AEO.
How AI models decide who to mention
Unaided mentions are not random. Training-data frequency, prompt shape, list effects, and known biases all influence who surfaces in an AI answer — and all of them can be observed in a controlled test.
Analyzing occupational bias in LLM recalls
A data study summarizing how different professions surface differently across models. Standardized prompt categories reveal distinct visibility clusters for athletes, actors, and tech CEOs.
Generative Engine Optimization (GEO): the complete guide to AI model visibility in 2026
Search behavior is shifting from blue links to conversational answers. Learn how AI models decide which brands to mention and how to measure GEO performance.
Why ChatGPT, Claude and Gemini recommend different brands
The same category prompt produces different brand lists across models. Training data, alignment, configuration and ordinary response variance all contribute — and all of it is measurable.