How do you measure whether AI is recommending you?
You ask the models the same questions on a schedule and record whether your business was named, on which platform, and in what pos…
How they ask
How do people actually ask an AI for a local business?
The short answer
In three shapes. The recommendation ask wants curation and expects two or three names. The problem ask describes a symptom rather than a service, so the model must work out the trade first. The verification ask happens after someone already has your name — and it is the one most businesses lose without ever finding out.
Branded, Claude30 of 30 probes
Branded, ChatGPT18 of 26 probes
Unbranded, Gemini0 of 64 runs
01 · Why
Why it matters
They are three different competitions, and they have different winners.
The shape decides who wins
These are not three phrasings of one question. They are three different competitions with different winners.
A recommendation ask is a contest between businesses in a category. A problem ask is first a classification task and only then a contest. A verification ask is not a contest at all — it is a single business being checked, and the only outcome is confirmed or not confirmed. Being strong at one says very little about the others.
Verification is the one that quietly costs you
It is worth dwelling on, because it is the one that already affects every business with any marketing at all.
Somebody sees your van, gets a postcard, is handed your name by a neighbour. Twenty years ago they called. Now they ask an assistant whether you are any good. If the answer is confident and positive, your existing marketing just worked. If it is vague — "I don't have specific information about that business" — the referral quietly dies, and nothing in your analytics records that it happened.
The referral quietly dies, and nothing in your analytics records that it happened.
02 · What
What it actually is
What we actually measure across the three shapes.
What the data says about each
We probe these weekly, so this is measurement rather than theory.
Verification asks are winnable now. Across the live sites we run, asked about a business by name, Claude named it in 30 of 30 probes, ChatGPT in 18 of 26, Gemini in 18 of 26.
Open discovery asks are much harder. On unbranded questions like "best HVAC company near West Palm Beach", the same businesses are named far less often, and on Gemini they were not named at all across 64 runs.
We would rather tell you that than sell you the easier story.
03 · How
How it works
What answering each one requires.
Answering all three
The verification ask needs an authoritative record about you specifically — enough structured detail that a model can answer confidently instead of hedging.
The problem ask needs your reviews analysed by problem, not just by service, so that "water heater making a banging noise" connects to you rather than only "plumber" connecting to you.
The recommendation ask needs everything the other two need, plus being discoverable in the first place — indexed, submitted, and present in the sources a model reaches for. It is the hardest of the three and the one we are most careful not to overclaim.
04 · Questions
Common follow-ups
Which of these should I care about most?
Verification, if you do any outbound marketing at all. It is the ask that decides whether the money you already spend converts, and it is the one we can most clearly demonstrate.
Do people really describe symptoms instead of services?
Constantly — it is most of the natural-language advantage. 'Strange smell from the AC vents, who do I call' is a real probed prompt, not a hypothetical.
How do you know what people ask?
We probe a panel of prompts per client weekly against Claude, ChatGPT and Gemini, and record what came back. The prompts on each industry page are real rows from that, with their dates.
Start where AI starts
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