InsightsAI visibility
Measuring AI visibility means counting whether systems name your brand, or use you as a source, on the questions that matter.
Sessions alone say too little: an Overview can take the click while you are still cited.
Mentions: is the brand name used? Citations: is your URL, or a paraphrase of your block, in the answer? Coverage: on how many of your core questions does that happen?
Palan runs those questions on a schedule in ChatGPT, Perplexity and Google. No endless tool stack. A fixed set of prompts, the same each round, or you are not comparing anything.
Per question: named or not, as a source or only a paraphrase, and who the competitor is. Under that: which page is missing or too weak.
The report is a backlog, not a vanity dashboard. Palan ties each gap to a URL to make or rewrite. Numbers with no next page are a presentation.
You measure AI visibility by running a fixed set of questions through answer systems and scoring whether your brand is named or cited. Palan turns the gaps into content work: which page, which passage. Rankings still exist. They are no longer the only count.
Dashboards keep appearing. None of them replaces a fixed question list you understand. Palan measures with repeatable prompts plus what the market offers, not with a black box as the only truth. The question set is the instrument.
Monthly is enough to see direction without drowning in noise. Answers change by the day. Palan looks at the trend per question, not at one screenshot. Weekly panic is not reporting.
Sometimes, when there is a click. Often not. That is why we count mentions separately. Palan reports both: traffic where it exists, citations where the click is missing. Reading only analytics misses half the game.
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