How we sample answers, what we do with the numbers, and where the measurement stops.
Chart how often ChatGPT, Gemini and Google's AI answers name your brand, beside Google Analytics, in Data Studio (formerly Looker Studio). One-click template included.
We tested AI search volume on 308 phrases against Google. It is modelled from Google, counts words not questions, and inflates ordinary words. Data included.
We asked ChatGPT 100 buying questions in its interface and through the API. The brands mostly matched; the cited sources overlapped 8% of the time. Data included.
Every Otterly.AI plan and engine add-on, and what four real setups cost per month once Gemini, AI Mode and Claude are added. Checked 10 October 2026.
Connect Claude Code to Recomma over MCP, read the site audit's findings, fix the template, close the ticket — and let the re-measure say if it worked.
The fifteen markup rules our site audit runs on every page, in queue order: what each checks, why an engine cares, and the fix that fits in a diff.
The share of AI answers that name your brand, plus share of voice, position and sentiment — each defined the way it is counted, and over what.
Same keyword data, different result: an answer that names a few brands, not a list of pages. What carries over from SEO, and what does not.
How an AI answer becomes a number: captured from the interface a reader sees, sources kept as shown, and 'named' kept apart from 'cited'.
Closing a ticket freezes a baseline; fourteen days later the same prompts are re-measured on fresh answers. The verdict is kept even when nothing moved.
A visibility percentage without a sample size is a coin flip with a decimal point. Every metric here carries the answers behind it and a 95% Wilson interval.