Methodology
What we measure, and what keeps it honest.
The same methodology runs on our own market every month and the results are public. Here is what a Saymetry run measures, and the rules that keep the numbers honest.
01
We measure answers, not rankings
A Saymetry run asks the AI engines the things real buyers in your market ask them, and records what comes back: every name recommended, every name mentioned, every source cited. How we design and target those question sets is our craft and stays ours; what you can always verify is the output, because your report shows every question asked, verbatim, next to how every engine treated it.
02
Eight engines, as buyers meet them
Every run covers ChatGPT, Claude, Gemini, Perplexity, Grok, DeepSeek, Mistral and Llama. Where an engine supports live web search, the run uses it, because that is how the deployed assistants actually answer buyers; where it does not, the answer is measured as the engine gives it, and the report says which was which.
03
Recommended, mentioned, cited: three different things
Being named is not being endorsed. We score every answer three ways: recommended (the engine steers the buyer to you), mentioned (you appear at all), and cited (your own pages are used as a source). The gaps between the three are usually where the actionable work hides.
04
Counts before percentages
Numbers are reported as plain counts first ("recommended in 12 of 45 questions"), because counts are checkable and percentages hide sample sizes. Where a run cannot classify enough answers to be trustworthy, it is held and re-run, never padded.
05
The conflict firewall
We sell measurement, and we sell remediation. We never sell rankings. The public index at claw.mobile covers the AI builder market; for that market we sell measurement and clearly disclosed media only, never remediation, so a ranked vendor can never pay us to move a number. Scan and report results are never adjusted for any commercial relationship, and no one can pay to change them.