AI search & visibility

AI Visibility

AI search visibility

How often and how accurately a brand, product or website appears in the answers that AI assistants and AI search engines give.

FOUR MEASURES OF AI VISIBILITYMentionsshare of answers that name your brandCitationsshare of answers that link to your siteSentimentwhether you are described positively, neutrally or negativelyAccuracywhether what is said about you is trueAnswers vary from run to run: measure by regular sampling of fixed questions, never from one screenshot.

swipe to see the whole diagram →

MEmehmeterkek.com/glossary/ai-visibility

In plain terms

When a buyer asks an assistant “which accounting software should a small company use?”, a handful of names appear in the answer. AI visibility is the question of whether yours is among them, whether your site is linked as a source, and whether what is said about you is positive and true.

Why it matters

A growing share of research and buying decisions starts with a question to an assistant, and the answer is a short list where a results page once offered ten links. There is no page two. Visibility here is not shown in classic web analytics, because being mentioned does not produce a visit. It has to be measured on purpose. The accuracy measure deserves particular attention: assistants repeat outdated prices and discontinued features with complete confidence.

Example

An accounting software firm tests 50 typical buyer questions on four assistants, five runs each, every month. It is named in 18% of answers and its main rival in 46%. Two causes emerge: assistants quote an old price taken from a 2023 review, and none mentions the e-invoicing module, which is described only in a PDF. Both are fixed. Three months later the figure is 31%.

Most often confused with

AI Visibility vs. Search ranking

AI VisibilityA share of answers, measured by sampling
Search rankingA position on a results page

A ranking is a position you can look up: third for this keyword. AI visibility has no fixed position, since the same question produces different answers on different runs, for different users and on different assistants. It is a rate, and it is measured the way a poll is: with enough samples.

Under the hood

Common measures: mention rate, citation rate, share of voice against competitors, position within the answer, sentiment and factual accuracy, each per assistant and per question set. Method: fix a set of questions that reflects how buyers really ask; run each several times on each assistant, with web search on and off where possible, in the relevant languages and countries; record and compare over time. Limits: platforms publish little data of their own, samples are noisy, and results depend heavily on the questions chosen. What moves the figures: access for AI crawlers, clear and current facts on your own site, and presence in the third-party sources that assistants draw on, such as reviews, comparisons, reference sites and forums. Referral visits from assistants in your analytics are a useful second signal.

Written by Mehmet Erkek · Last updated: