# LLM Visibility Tracking

> LLM Visibility Tracking is the measurement of AI visibility: prompts are sent to AI systems and the answers are analysed for mentions and citations of the brand, as a probability across many runs rather than a position.

Source: https://www.codaai.ai/en/knowledge/geo-glossary/llm-visibility-tracking/
Published: 2026-09-03
May be quoted with attribution and a link to the source.

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LLM Visibility Tracking is the measurement of whether and how often a brand appears in the answers of AI systems. A fixed set of prompts ([prompt set](https://www.codaai.ai/en/knowledge/geo-glossary/prompt-set/)) is sent regularly to ChatGPT, Gemini, Perplexity and other systems; each answer is analysed for whether the brand is mentioned ([mention](https://www.codaai.ai/en/knowledge/geo-glossary/mention/)) or cited as a source ([citation](https://www.codaai.ai/en/knowledge/geo-glossary/citation/)). The result is not a position but a probability.

## How does LLM Visibility Tracking differ from SEO rank tracking?

| | SEO rank tracking | LLM Visibility Tracking |
|---|---|---|
| How is it measured? | Keyword sent to a search engine; the result is a list with positions 1–100 | Prompt sent to an LLM; the synthesised answer is analysed for mentions/citations |
| How stable is the result? | Reproducible: the same keyword, location and time yield largely the same list | Every query is unique; stochasticity and personalisation change the answer on every run |
| What is measured? | Objective position in an index, an absolute value | Tendency across many runs, a statistical approximation |
| Example insight | "For keyword X, I rank at position Y in Google DE mobile." | "In topic area X, I am mentioned in 40% of the answers to my proxy prompts." |

## Why does LLM Visibility Tracking matter?

Because traffic and rankings do not reflect AI visibility: the decision is made in the answer, before the click. Without your own measurement, it remains invisible whether a brand appears in the questions its customers ask, and whether measures are working. A single value is worthless; only the trend over weeks and the comparison with competitors ([Share of AI Search](https://www.codaai.ai/en/knowledge/geo-glossary/share-of-ai-search/)) produce a picture.

## What does this mean for your website?

Define a prompt set along the customer journey, run a [baseline measurement](https://www.codaai.ai/en/knowledge/geo-glossary/baseline-measurement/) and then measure regularly: every question several times, in all relevant systems. Collect [Mention Rate](https://www.codaai.ai/en/knowledge/geo-glossary/mention-rate/), [Citation Rate](https://www.codaai.ai/en/knowledge/geo-glossary/citation-rate/) and [Sentiment](https://www.codaai.ai/en/knowledge/geo-glossary/sentiment/), supplemented by the Search Console and Bing reports and the [log files](https://www.codaai.ai/en/knowledge/geo-glossary/log-files/). The Digital Visibility Audit by CodaAI follows exactly this pattern with company-specific buyer questions.