Stop when the answers to your buyer questions are correct and nothing is pending on them, and decide that in advance rather than when the invoice arrives.
Of the four things worth writing down before measuring anything in this category, the stop condition is the one people skip. The buyer question gets written. The decision gets named. The evidence threshold sometimes gets set. Almost nobody writes down when to stop.
A check with no end condition is not a check
It is an ongoing commitment, and an ongoing commitment behaves differently from a one-time question.
A measurement that renews has to keep feeling worth renewing. That creates quiet pressure for the number to visibly move, which selects for metrics that are sensitive rather than metrics that are valid. A figure that jumps around looks alive. A figure that sits still looks like something you could cancel.
The honest version of most answer quality checks produces a boring result. The answers were right, nothing needs doing, look again in a quarter. That is the outcome you want and it is the hardest one to build a recurring product around.
Naming the stop condition first is what protects the measurement from that pressure.
What a stop condition looks like
Two branches, written before the first check runs.
If the answers come back correct. Stop. Record what was asked, which engines, the date and what they cited, so the next reading is comparable. Look again in a quarter, or sooner if something changes on your side that would alter the correct answer, such as a new tier, a new integration or a change in what the product actually does.
If the answers come back wrong. Confirm it clears your threshold first, which for most questions means the same wrong answer appearing in at least two of ChatGPT, Claude, Gemini and Perplexity on the same question asked the same way. Then correct the source, and recheck those same engines on the same question after a set interval. Thirty days is a reasonable default.
Then stop again. The recheck has an end too.
The reason to name the specific engines rather than writing “the major assistants” is that the set changes and your record needs to survive that. If you checked four and only name three a year later, you have lost the ability to tell whether the fourth was ever correct.
Why the recheck interval has to be fixed in advance
Because a recheck run whenever somebody feels nervous is not a comparison.
If the question changes, the engines change, or the conditions change between readings, you have collected a new observation rather than measured a difference. You will not be able to tell whether the answer moved or whether you asked differently.
Fixing the interval and the conditions beforehand is what makes the second reading mean anything.
What a recheck cannot establish
It cannot establish that your fix worked.
If you revise a page and the answer improves thirty days later, that is consistent with your change having worked and also consistent with the model version changing, retrieval changing, or the set of sources an engine reaches that day changing.
To get closer, recheck comparable observations under the same conditions and look at whether the revised page is among the sources the new answer draws on. If the revised page is not visible among the sources, you cannot establish whether it contributed. Even a citation would not, by itself, prove the change caused the improvement.
This is worth saying plainly because the opposite claim is common and it is not supportable from outside the system.
Signals that it is time to stop entirely
Four of them, in rough order of how often they apply.
No decision is pending. You wrote down what you would do differently depending on the answer, and the honest version is nothing. Stop now rather than at renewal.
The answers have been correct across three consecutive checks. Whatever risk you were watching for is not materialising on these questions. Reduce the cadence or stop and set a reminder tied to product changes instead of to the calendar.
The number you are watching has no threshold attached. If no value of it would cause you to act, it is a report rather than a measurement.
The only thing the measurement produces is movement. If every reading differs and none of the differences has ever changed a decision, you are measuring variance.
An empty list is a legitimate finding
The most useful outcome of this discipline is sometimes concluding there is nothing here worth watching this quarter.
That takes minutes to establish and it is the finding almost nobody in this category will volunteer. It is also the one that makes the remaining measurement credible, because a process capable of returning nothing is a process whose findings mean something when it returns something.
Frequently asked questions
How often should I check what AI says about my product?
Set the interval before the first check. A quarter is reasonable when answers came back correct, and thirty days is reasonable when rechecking after revising a source.
What if I stop measuring and something changes?
Tie the next check to a product change rather than to the calendar. A new tier, a new integration or a change in capability alters what the correct answer is, which is a better trigger than a date.
Is continuous AI visibility monitoring worth it?
Only where a decision depends on movement. If no value of the metric would change what you do, continuous monitoring produces reporting rather than information.
How do I know whether my fix changed an AI answer?
You cannot establish it from outside with certainty. Recheck under the same conditions and look at whether the revised source appears in the new answer, treating absence as unresolved rather than as evidence either way.
What should I keep after I stop measuring?
The question as asked, the engines, the dates, the conditions and what each answer cited. Without that record the next check restarts rather than continues.
Does stopping mean AI visibility does not matter?
No. It means the specific questions you checked came back correct and nothing is pending on them, which is a result about those questions rather than a verdict on the category.
ABOUT AXIS SUITE
Axis Suite by TrendAxis is the independent intelligence layer that explains what AI believes about your brand, why it believes it, and what decision that belief ultimately drives. See the recorded observations and the method behind them at axissuite.ai and in the Proof Center.