AI Search Optimization

What a Good AI Visibility Score Looks Like (and How to Read Yours)

Published July 27, 2026

An AI visibility score answers one question: when your buyers ask an AI assistant who to hire, how often is it you? A single number hides the story behind that answer. This guide breaks down the five categories behind the score, what each one measures, what a good number looks like at your stage, and which gap to fix first.

What does an AI visibility score actually measure?

An AI visibility score is a rollup of five scored inputs: how often AI assistants name your business across a fixed panel of buyer prompts, how much of the answer space competitors take instead, the tone of the mentions you do get, whether the description AI gives is accurate, and where in the answer you appear. The sources AI cites are reported alongside the score rather than folded into it.

• Mention rate: how often you're named across a fixed panel of buyer prompts, run the same way each time so the number is comparable month to month.
• Share of voice: your presence relative to the competitors AI names instead. Appearing in one answer out of ten means something different when a single rival owns the other nine.
• Sentiment and accuracy: whether AI describes you correctly and favorably. A confident wrong answer (old hours, a service you dropped, the wrong city) costs you about what no answer costs you.
• Citations: the third-party sources AI leans on when it answers. These are reported alongside the score rather than scored, and they tell you where the answer is coming from, which is where the work has to happen.

None of this is a ranking you can look up. No provider publishes a leaderboard for AI answers, and the same prompt can return different names on different days. That is why the panel matters more than any single run: fixed prompts, asked on a schedule, so you are reading a trend instead of a coin flip.

What are the five categories in the free Visibility Check?

Five categories make up the composite in our free Visibility Check. AI Visibility is the headline: are you in the answer at all? Review Presence, Structured Data, and Citation Footprint are the other three scored inputs, weighted into the composite rather than into whether you are named. Ad Presence covers whether you are set up to capture the clicks that remain when an AI answer does not close the buyer.

• AI Visibility: the headline number. Whether assistants name you when someone asks who to hire in your category and your market.
• Review Presence: whether your Google Business Profile link and the review platforms your site connects to are there for the buyer who checks you after an answer names you. What buyers check after AI names you is a subject of its own.
• Structured Data: whether AI can parse and trust your site. Schema markup, facts that agree with each other, and a readable orientation file.
• Citation Footprint: in the free check, an estimate from your AI mention rate and the review-platform links on your site; the paid audit measures citations directly. Your own site claiming something counts for less than three other sites repeating it.
• Ad Presence: whether you are positioned for the clicks that remain. AI answers do not end the search, and plenty of buyers still click through.

Read the categories before you read the composite. Two businesses can land on the same overall number with completely different problems: one invisible in answers but well reviewed, another well cited but unparseable. The fix list is different in each case, and the composite alone will not tell you which one you are.

What counts as a good AI visibility score?

Good depends on your stage, not on a universal cutoff. Below roughly 30, you are not in the conversation and the priority is fundamentals. Between 40 and 60, you appear sometimes while competitors take the rest. Above 70, you are a default answer and the job shifts to widening the lead.

Context sets the bar. A 55 in a crowded metro, where many firms compete for the same sentence of the same answer, is a stronger position than a 55 in a thin rural market where only a few names exist at all. Compare yourself to the businesses AI names instead of you, not to an average.

What should you fix first?

Fix in cost order, cheapest high-impact work first. Profile accuracy, consistent business facts, and schema take hours rather than months, and they unblock everything downstream. Citations come next because they accumulate slowly, and a steady review cadence runs alongside them for the buyer who checks your reviews once an answer has named you. Content for the prompts where you are absent comes last, once AI can parse and trust you.

1. Clean the fundamentals. Start with your Google Business Profile, NAP consistency across every listing, and schema that states your facts in a form machines read. A wrong fact here gets repeated everywhere else.
2. Build the outside evidence. Independent citations are third-party corroboration, and reviews are what the buyer checks after the answer. Both are slow, so start them early.
3. Publish answer-ready content for the prompts where you're absent. Look at which panel prompts return competitors, then write the page that answers that question directly. Getting cited by ChatGPT and Perplexity covers the format.
4. Re-score monthly. A score you check once is trivia. A score you check on a schedule is a managed number, and it tells you whether last month's work landed.

Skipping ahead to step three is the common mistake. Publishing into a site AI cannot parse, or one whose facts contradict your listings, buys very little. We verify what AI can currently read about a business before writing a word of new content, because the reading problem is usually cheaper to fix than the writing problem.

Want your own number? Run the free Visibility Check for a first read on where you stand, or get the full audit if you want the roughly 25-prompt version with a full gap analysis and a prioritized fix plan.

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