Answer

How often should I check my AI visibility?

The short answer

Check your AI visibility monthly if you are not changing anything, weekly while you are. Checking daily tells you more about the randomness in the engines than about your business. What matters far more than frequency is consistency: the same questions, the same engines and the same wording every time, so that a change in the result means something actually changed in the world.

Answered 1 August 2026Method: The Receipts EngineAnswerable sells monthly monitoring: read this as an interested party

The cadence that suits most businesses

Monthly. It is long enough for a real change to appear and short enough that you can still connect the change to whatever you did.

The reasoning is about how slowly the inputs move, not about how often the engines answer. The things that shift whether an assistant names you, a run of new reviews, a directory listing going live, a roundup article publishing, a page being rewritten and recrawled, take weeks to exist, be crawled and be reflected in what an engine retrieves. Sampling faster than the inputs change buys you noise.

Two disclosures, since we are recommending a cadence and we sell one. Answerable's monitoring product re-scans each client once a month on their own scan day, so this recommendation matches what we sell. And that product is built rather than operating: as of writing it has not been deployed. Both facts are stated on our technology page.

When weekly is worth it, and when it is theatre

Weekly is worth it while something is genuinely in motion, and it is theatre when nothing is.

When a weekly check earns its time, and when it does not
SituationWeekly?Why
You are mid-way through a fix engagementYesThings are changing weekly, so the measurement should be able to catch them and attribute them.
You have just unblocked AI crawlers in robots.txtYes, for a monthThis is the one change with a plausibly fast effect, because it stops removing you from live retrieval.
You have rebranded, changed trading name or moved domainYes, for a month or twoEntity confusion is the risk, and it shows up in the direct question fast.
Nothing has changed since your last checkNoYou will be reading sampling variation and calling it a trend.
You are checking one question because it worries youNoA single question is the noisiest possible measurement. Run the whole set or none of it.
You are checking because a competitor was named onceNoOne answer naming a competitor is one sample. Check the rate next month.

Why daily checking misleads

Daily checking measures the randomness in the engines more than it measures your business. The same question asked twice in an hour can return different businesses in a different order, because the model samples its output and the pages it retrieves move underneath it. The mechanism is set out in why AI answers change every time you ask.

Three practical consequences:

  • Nothing you do on a Tuesday is crawled, indexed and reflected in an answer by Wednesday. The input side simply does not move that fast.
  • A daily series will show movement in every direction, and a human reading it will find a story in it. That story will usually be wrong.
  • Daily monitoring is the easiest thing for a vendor to charge for and the hardest thing for it to justify. Anyone selling realtime AI rank tracking is selling a sampling artefact.

We sell monitoring, so here is the version that costs nothing

Answerable sells monitoring at $199 a month, so treat this section as the version to use if you would rather not pay us. It takes about fifteen minutes a month and a spreadsheet.

  1. Write five buyer questions the way a customer would say them, in your category and your city, with your business name in none of them. Save the wording and never edit it.
  2. Write one direct question: what do you know about [business name] in [city]. Keep it separate from the five.
  3. Once a month, in a fresh chat with memory off, ask all six of ChatGPT and all six of Gemini.
  4. Paste every answer into the sheet in full. Not a summary, the whole reply.
  5. Record whether you were named in each of the five, and where in the list you appeared.
  6. In the same row, write down what you changed since last month.

That is the whole method. It produces a rate with a denominator, a stored transcript and a change log, which is most of what a paid report should be giving you anyway. What you are paying a vendor for is that it happens without you, the same way every time, with alerting when it moves. If you want to compare that against what people charge, what AI visibility costs in Australia lists the four bands.

What to record each time so the history is worth having

Record the question verbatim, the engine, the date, whether you were named, and the whole answer text. Anything less and next year's version of you cannot audit this year's.

The fields to record on every check
FieldWhy it has to be there
Date of the runEvery one of these figures is a snapshot. A figure with no date cannot be compared to anything.
Engine, and whether search was onA grounded answer and an ungrounded one are different measurements and must not be averaged.
The question, word for wordRewording is the easiest way to fake an improvement. The verbatim text is the audit trail.
Named: yes or noThe count. This is the 70% of the thing that a third party can reproduce.
Position in the list, if there was a listNamed seventh of seven and named first are not the same result.
The complete answer textThe transcript carries what the score cannot: wrong suburb, old price, cited source, hedged non-answer.
What you changed since last timeWithout this you have a chart with no causes, and you will invent one.

Once you have three or four of these rows, you can start reading progress honestly. What that looks like is covered in how to know if AI visibility work is actually working.

Start the history today.

The free scan gives you a dated baseline across ChatGPT and Gemini, with one real quote of what an engine said about you. Keep it, and compare against it next month.

Run my free scan