Metrics

AI Visibility Score

A composite metric that summarizes how strongly a brand appears across AI answers, combining mention rate, position, and citation share into a single 0–100 number.

TL;DR

The AI Visibility Score is a single 0–100 number that sums up how strongly your brand appears across AI answers. It blends three signals, mention rate, position, and citation, into one figure a whole team can track.

0–100
a single, comparable index
3
signals feed the number
1/wk
track it weekly for momentum

Explain it like I've never heard of this

Think of a credit score. Behind it sit lots of little details , payment history, balances, account age, but you only ever see one number, and you instantly know if it's good or bad.

The AI Visibility Score works the same way. It takes how often AI mentions you, how early it mentions you, and whether it cites your site, then rolls them into one number from 0 to 100. Higher means AI talks about your brand more, sooner, and more credibly.

Diagram showing three input signals, mention rate, position, and citation, feeding into a gauge that reads 72 out of 100, representing a combined AI Visibility Score
Three signals, mention rate, position, and citation, combine into one gauge from 0 to 100. Here the brand scores 72: strong visibility.

The "AI Visibility Score" is just a quick way to answer: overall, how present is my brand inside AI answers right now?

Words you'll see, in plain English

A handful of terms come up whenever people discuss the score. Here's what each means.

AI Visibility Score

A single 0–100 number that sums up how strongly your brand shows up across AI answers, like a credit score for AI presence.

Index / composite

A score built by blending several smaller measurements into one easy-to-read figure.

Mention rate

The share of tracked questions where the AI names your brand at all.

Weighting

Giving more important prompts and models a bigger say in the final number, so it reflects what actually matters.

Commercial intent

Questions from people who are close to buying, e.g. 'best CRM for startups'. These count for more.

Benchmark

A reference point, your past score or a competitor's score, that makes a number meaningful.

How the score is built

Three signals feed the number. Each is weighted by how much it really reflects buying impact.

Signal 1

Mention rate

How often, out of all tracked prompts, the AI names your brand. The wider your mention rate, the higher the floor of your score.

Signal 2

Position

How early your brand appears in the answer. Leading the answer lifts the score; trailing at the bottom barely moves it.

Signal 3

Citation

Whether the AI links to your own domain as a source. Citations carry the most weight because they can drive real traffic.

Why a single score helps

You could stare at three separate charts every week, or watch one number and act on it.

One number, not a spreadsheet

Mention rate, position, and citation are hard to compare side by side. The score blends them into something a whole team can rally around.

It shows momentum

A score rising week over week after a content push is proof AI models are ingesting your material. A flat line is an early warning.

It's weighted for what matters

Commercial-intent prompts and high-share models like ChatGPT and Gemini carry more weight, so the score tracks revenue-relevant visibility.

It's comparable

Because it's a 0–100 index, you can compare yourself this month vs last month, or against named competitors, at a glance.

How to use the score

Track it weekly. A rising score after a content or PR push is a strong signal that AI models are ingesting and surfacing your new material. A flat or declining score during such a push is a warning that the content isn't being picked up by retrieval , a cue to check crawlability, structure, and third-party coverage before spending more on production.

Your AI Visibility Score checklist

  • The score blends mention rate, position, and citation, not just one signal
  • High-intent prompts are weighted above generic ones
  • High-share models (ChatGPT, Gemini) carry more weight than niche ones
  • The score is tracked weekly to spot momentum early
  • Each score change is tied back to a content, PR, or technical action
  • Competitor scores are tracked alongside your own for context
  • A flat or falling score during a push triggers a retrieval check

See how your brand performs across AI assistants

Strajist tracks your visibility, share of voice, and citations across ChatGPT, Gemini, Claude, Perplexity, and more.

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