An AI visibility score measures how often your brand appears in answers generated by ChatGPT, Perplexity, Google AI Overviews, Gemini, and Copilot across a fixed set of prompts your buyers would actually type. You build a prompt library, run it across engines on a schedule, record which brands get named, and express your appearance rate against a named competitor set. Without that competitor set you have a visibility number, not a share of voice.
Here is the methodology, the metrics that separate a good score from a vanity one, and how to run it without buying anything.
Why a single number is not enough
Most tools report one percentage. That number hides four different outcomes that mean very different things:
- Mention — your brand name appears in the answer.
- Citation — your page is linked as a source.
- Recommendation — the model actively suggests you as the answer.
- Absorption — your framing appears in the answer without attribution.
A mention is not a citation, a citation is not a recommendation, and a recommendation is not absorption. Being named in a list of eight tools is worth far less than being the one the model suggests. Track them separately or your score will improve while your pipeline does not.
Step 1 — Build the prompt library
Between 30 and 100 prompts, split across three clusters:
| Cluster | Example | What it tells you |
|---|---|---|
| Branded | "Is [your brand] any good?" | How the model characterizes you — sentiment and accuracy |
| Category | "Best tool for [job to be done]" | Whether you make the shortlist at all |
| Comparison | "[Your brand] vs [competitor]" | How you are positioned against named rivals |
Weight the category and comparison clusters most heavily. Those are the prompts that decide purchases; branded prompts mostly tell you whether the model has your facts right.
Write the prompts the way a buyer types them, not the way you describe your product. "Best tool for finding customers on Reddit" is a real prompt. "Reddit-native AI-powered engagement platform" is not.
Step 2 — Name your competitor set
Pick three to five named rivals and hold the list constant. This is the step that converts a visibility number into a share of voice, and it is the step most people skip.
Step 3 — Run the prompts consistently
Same prompts, same language, same competitor set, same engines, on a schedule. Full audits monthly, spot-checks on your top prompts weekly — citation distributions shift within weeks as models update and indexes refresh.
Two things will corrupt your data if you let them: personalization (run prompts in a fresh session, logged out where possible, with memory disabled) and drift (rewriting a prompt mid-quarter makes the time series meaningless).
Step 4 — Score it
The base calculation is a weighted share:
AI share of voice = (your weighted citations) ÷ (total weighted citations across all tracked brands) × 100
Weighting is what makes it useful. A recommendation should count for more than a passing mention, and a category prompt should count for more than a branded one. A workable scheme:
| Outcome | Weight |
|---|---|
| Recommended as the answer | 3 |
| Cited with a link | 2 |
| Mentioned by name | 1 |
| Absent | 0 |
| Mentioned negatively | −1 |
Track the five underlying metrics alongside the composite: citation rate, mention rate, recommendation rate, citation absorption, and sentiment. The composite tells you whether you are winning; the components tell you what to fix.
What a score actually looks like
Absolute benchmarks are not very meaningful across categories — a crowded software category behaves nothing like a niche B2B one. What matters is the delta: your score against the same competitor set, over time. A move from 8% to 14% share of voice in a quarter is a real result. "14%" on its own is not interpretable.
How to move the number
Your score is mostly determined off your own domain. Brands are substantially more likely to be surfaced through third-party sources than through their own site, because generative engines answer by consensus rather than by taking a homepage at its word.
- Get named in the listicles that rank for your category. These are among the most-read sources when a model assembles a shortlist.
- Maintain review-platform presence. G2, Capterra, AlternativeTo and their equivalents in your space.
- Show up on Reddit. A Semrush analysis of 150,000 AI citations found 40.1% pointed at Reddit — more than Wikipedia and YouTube combined. If your category is discussed there and you are never named, that alone caps your score.
- Make your own pages extractable. Direct answers, tables, schema, visible dates. This is what turns a mention into a citation.
- Keep your entity facts consistent. Conflicting descriptions of what you do across the web produce vague, low-confidence answers.
Our free AI visibility checker runs the live citation check across ChatGPT and Perplexity, and RedditGrow covers the lever most teams cannot move manually — being present in the Reddit threads those answers are assembled from.
Common mistakes
- Measuring branded prompts only. Of course the model knows you when you name yourself. That is not visibility.
- Changing the prompt set every month. You lose the time series, which is the only part that means anything.
- Ignoring sentiment. Being mentioned as the expensive option is not a win.
- Running prompts in a logged-in session. Personalization and memory inflate your own results.
- Treating one engine as all of them. ChatGPT and Copilot lean on the Bing index; AI Overviews lean on Google rankings. Different inputs, different outcomes.
Frequently Asked Questions
What is a good AI visibility score?
There is no universal benchmark — it depends entirely on how crowded your category is. What matters is the trend against a fixed competitor set. Measure monthly and judge the delta, not the absolute number.
How many prompts do I need to measure AI visibility?
Thirty to a hundred, split across branded, category, and comparison clusters. Fewer than thirty produces noisy results; more than a hundred is hard to sustain monthly without automation.
How often does AI visibility change?
Faster than search rankings. Citation distributions can shift within weeks as models update and indexes refresh, which is why monthly full audits with weekly spot-checks is the usual cadence.
Can I improve AI visibility by changing my own website?
Partly. On-page structure — direct answers, tables, schema — turns mentions into citations. But most of the score is determined by third-party sources, particularly listicles, review sites, and Reddit.