Measurement Notes
Notes on experimental design, comparability, repetition and sample quality.
Research
Applied research into how AI visibility changes.
A home for methodological studies, aggregated benchmarks and observations about sources, models, prompts and recommendation behavior, with evidence boundaries made explicit.
Benchmarks
A publication layer for aggregated, anonymized benchmarks once responsible sample thresholds are met.
Source Observatory
Analysis of diversity, concentration and source consensus observed in grounded measurements.
Model Behavior
Studies of variation across models and contexts without presenting local observations as universal truths.
Evidence before claims
Measure your own brand instead of relying on generic assumptions.
M2 Visibility connects prompts, models, sources, competitors and confidence into a repeatable operating loop.