AI Search Visibility
AI visibility monitoring
Track how AI search describes your business over time: a fixed question set, observed mentions, citations and errors, and a regular summary.
The problem
Visibility changes without notice
Engines change their answers, and you find out only when someone mentions it.
Single checks mislead
One answer on one day says little about how you are represented overall.
What is included
A maintained question set
The agreed questions, updated as your offer and market change.
The engines we cover
The same engines checked each time, named in each summary.
Mentions, citations and errors
What changed in how you are named, cited and described.
A regular summary
What changed, what may explain it and what to consider next.
An example, step by step
Input
Question set
Twelve buyer questions in Dutch and English, asked in the same engines every month, three runs each.
- Run the questions and store every answer with its date and engine.
- Count mentions and citations, and flag wrong descriptions.
- Compare with last month and note what changed on your side and in the answers.
Output
A monthly summary
A synthetic chart of mentions per month, the wrong descriptions found, and two suggested actions; changes are reported as observed, not attributed without evidence.
How it works
Set up
We agree the questions, engines and how often to check.
Check
We run the questions on schedule and record the answers.
Summarise
You receive a short summary of changes and suggested actions.
What you receive
Regular summaries
Changes in mentions, citations and descriptions over time.
Flagged inaccuracies
Wrong or outdated statements about your business.
Suggested actions
What to look at next, if anything.
What it works with
The engines' public answers
Answers to the agreed questions, in the agreed languages.
Your change log
What you published or changed, so changes in answers can be read against it.
How we check it works
A stable baseline
The same questions, engines and languages each period; any change to the set is noted.
Variation shown
Run-to-run differences are reported, so a small change is not read as a trend.
Errors flagged
Wrong facts about you are listed with the answer they appeared in.
What to keep in mind
- Monitoring shows changes; explaining them is not always possible, because engines do not publish why.
- Answers vary between sessions, so trends over time matter more than single results.
What shapes the scope and quote
- The number of questions, languages and engines.
- How often the check runs.
- Whether the summary includes suggested actions or only observations.
Frequently asked questions
How often do you check?
As agreed in the design step, for example monthly. More frequent checks rarely add much, because answers vary between sessions anyway.
Can monitoring run without implementation work?
Yes. Monitoring can stand alone, or follow an audit and implementation.
Is the chart in the example real data?
No. It is synthetic, to show the format. Your reports use the answers we record for your questions.
Can monitoring prove that our changes caused an improvement?
Not on its own. Answers change for many reasons. We report what changed and when, next to what you changed, without claiming cause where the evidence does not show it.
Other services in AI Search Visibility
AI visibility audit
A baseline of how AI search describes your business today, with prioritised next steps.
AI-ready content optimisation
Clearer pages and answers built around the questions your buyers ask.
Technical SEO & AI readiness
The technical foundations search and AI engines need to read your site.
Brand authority & citations
Consistent, credible signals about your business beyond your own website.