AI search visibility metrics and KPIs: what to track

What is presence, or mention rate?

Presence is how often an assistant names your business across many answers. If an assistant names you in 20 of 100 relevant questions, your presence is 20 percent.

Measure it by asking the same real customer questions several times, across assistants, and counting the share of answers that include you. A single answer is noise; the rate across many is the signal.

What good looks like depends on your market. Being named in a clear majority of relevant answers is strong; single digits mean AI rarely brings you up. In one of our own checks, an established clinic sat at 19 of 135 answers, about 14 percent.

Peekl reports this as your headline number, the share of answers that named you, with the per-question detail behind it.

How many questions do you appear in? (coverage)

Presence measures the share of all answers that name you. Coverage measures something related but distinct: across how many different questions, and buying intents, you show up at all.

A business can post a decent presence by being named often for one popular question. Yet it can miss entirely on the others customers ask. Coverage catches that blind spot.

Measure it by grouping your questions by intent (best in your area, near a landmark, for a specific need). Then check where you appear and where you never do. The empty intents point at the demand you are missing.

Good is broad, even coverage across the intents that matter to you, not a single question carrying your whole score. Peekl shows which questions name you and which name only competitors, so the gaps are obvious.

What is share of voice in AI search?

Share of voice compares how often you are named against your competitors for the same questions. It answers a sharper question than presence alone: when a business could be recommended, how often is it you rather than them?

Measure it by counting your mentions against each competitor's across the same set of answers. A decent presence still loses if two rivals are named far more often.

Good is being at or near the top of your set. In the check above, assistants named the business 19 times and its top competitor 70, a share of voice tilted heavily the other way.

Peekl shows this as a you-versus-top-competitor split, plus the full ranked list of who gets named and how often.

Which sources get cited, and what is your share?

Citations, sometimes called AI citations, are the websites an assistant draws on to build its answer: directories, best-of lists, review sites. Your source share is how much of that citation activity points to places that carry you.

Measure it by capturing the cited sources behind each answer and checking which ones list you and which do not. The gaps are your to-do list.

Good means the dominant sources in your market cite pages that include you. If the top few directories never mention you, that is often the whole reason competitors get named instead.

Peekl records the sources behind the answers and flags the ones that feed answers where you are absent.

How does AI describe you? (sentiment)

Sentiment is the tone an assistant uses about you when it names you: positive, neutral or flagged. Being named is good; being named with a lukewarm or cautionary description is a softer problem worth catching.

Measure it with sentiment analysis across many mentions, with a confidence on each read, rather than reacting to a single quote. It is a secondary signal and a decision aid, not fact.

Good is a consistently positive tone with enough mentions to be reliable. Peekl reports a sentiment read with real example phrases, and only when there are enough mentions to trust it.

How do the metrics differ by assistant?

AI visibility is not one number. One assistant can name the same business often while another ignores it, so a per-engine breakdown matters.

These AI models weight sources differently. Gemini leans heavily on Google's own signals. So your Google Business Profile and reviews shape your Gemini visibility metrics more directly than your ChatGPT results.

Measure each assistant separately, then compare. A strong overall number can hide a zero on the one your customers use most.

Peekl breaks every metric down by assistant, so you can read your Gemini visibility next to your ChatGPT and Claude results, not blended into a single average.

How do you track these metrics over time?

AI answers change from week to week, so a one-off snapshot ages fast. Tracking the metrics above over time turns a lucky or unlucky day into a trend you can trust.

The value of historical data is direction: are you named more often, are new sources starting to cite you, is a competitor pulling ahead? When you compare software for AI search optimization historical data, look for clean per-metric trends over time, not just a single current score.

Peekl's monthly tracking re-runs your check and charts presence and sentiment over time, and alerts you when you appear or disappear from answers.

How is this different from traditional SEO metrics?

Traditional SEO metrics answer a different question. Rankings, impressions, click-through rate and conversion rate all describe how you do on a page of links, and tools like Google Search Console report them well.

AI visibility metrics describe something those tools cannot see: whether an assistant names you in its AI generated answers, and how you compare there. You can rank well on Google and still be absent from the short list an assistant reads back.

So treat them as a separate layer, not a replacement. Keep watching your search metrics, and add these to see how you show up when customers ask an assistant instead of searching.

What about AI Overviews?

You may also see AI Overviews, the AI answers at the top of Google's results. Ranking in them follows similar logic to the metrics above: strong, well-sourced pages and consistent listings help, and there is no switch that guarantees inclusion.

It is a narrower, faster-changing surface than assistant recommendations, so treat it as one more place the same fundamentals apply, rather than a separate strategy.

Common mistakes when tracking these metrics

A few mistakes make the numbers lie. Fixing them matters more than adding another metric.

• Measuring once. AI assistants vary run to run, so a single check is a snapshot, not a trend.
• Checking one assistant. A strong ChatGPT number can hide a zero on Gemini, where your customers may actually be.
• Using generic prompts. Real-world questions your customers ask reveal far more than textbook queries.
• Watching the score, not the sources. A number without the AI citations behind it tells you where you stand, not what to fix.

Which tools measure all this?

You do not need to track these by hand. A good tool runs the questions, records every metric, and shows the sources behind them. For an honest, side-by-side look, see the best AI visibility tools compared.