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# Metrics reference

Exact definitions of every number in your report — AI Presence Score, coverage, visibility rate, win rate, and sentiment — and how each is computed.

This page is the precise definition of every metric in KnitKnot. Each is computed once at scoring time and read everywhere, so a headline number and the evaluations behind it never disagree. Throughout, an **evaluation** is one scored AI response — one prompt run against one engine.

## AI Presence Score

A **0–100 composite** of how favorably AI represents you across a benchmark, written at scoring time. It folds together how prominently you appear, whether you win comparisons, whether what AI says is accurate, and how favorably you're framed. It is a composite, not an average of the metrics below — those measure single dimensions; the score weighs all of them together.

Read the trend, not the absolute. See [The AI Presence Score](/docs/ai-presence-score/) for how the dimensions combine and why run-to-run variance is normal.

## Coverage

A **categorical label on each evaluation** describing how present you are in that one response. One of five values, most to least prominent:

  • - **Primary** — you're the main subject of the answer.
  • - **Substantial** — you're discussed at length, but not the sole focus.
  • - **Peripheral** — you're mentioned with some detail among others.
  • - **Incidental** — a passing mention.
  • - **Absent** — you don't appear at all.

Coverage is per-response and categorical. It's the raw material the visibility rate is built from — it is not itself a percentage.

## Visibility rate

The **share of scored evaluations where coverage is not `absent`** — i.e. how often you show up at all. A fraction from 0 to 1, shown as a percentage.

One critical detail: your report computes visibility **organic-only**. Head-to-head prompts that name your company directly (e.g. "Compare X vs Y") are excluded, because an AI mentioning you only because the question forced it to isn't real presence. What's left measures how often you surface when a buyer asks an open question about the category.

## Win rate (W-L-T)

For head-to-head comparisons, each evaluation resolves to one outcome: a **win**, a **loss**, a **tie**, or **not compared** (the prompt wasn't a comparison, or AI made no call). **Win rate = wins ÷ decided**, where *decided* = wins + losses + ties. **Ties count in the denominator** — a hedged answer is not a win.

Two rules shape this:

  • - Outcomes come from AI's actual pick in the response, extracted per feature and overall — not a holistic guess.
  • - A recommendation of one of your own products over another is a **brand win**, not a loss. Scoring understands your product family. See [Subjects](/docs/subjects/).

Win rate is also available per competitor and per feature, over the same underlying outcomes.

## Sentiment

How favorably you're characterized when you do appear, aggregated to a **0–100 scale** (higher is more favorable). Sentiment is measured per response and rolled up; it's independent of coverage — you can be highly present with lukewarm sentiment, or briefly mentioned in glowing terms.

## How they relate

  • - **Coverage** feeds **visibility rate** — coverage is the per-response label, visibility is the fraction of responses that aren't absent.
  • - **Visibility**, **win rate**, **accuracy**, and **sentiment** are the dimensions the **AI Presence Score** composites into one number.
  • - Every metric drills to its evidence: score → evaluations → response text → claim → cited source. See [Runs and scoring](/docs/runs-and-scoring/).

Raw mirror of this content: https://knitknot.ai/docs/metrics-reference.md. Site-wide summary: /llms.txt · full content: /llms-full.txt

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Metrics reference

Exact definitions of every number in your report — AI Presence Score, coverage, visibility rate, win rate, and sentiment — and how each is computed.

Updated

This page is the precise definition of every metric in KnitKnot. Each is computed once at scoring time and read everywhere, so a headline number and the evaluations behind it never disagree. Throughout, an evaluation is one scored AI response — one prompt run against one engine.

AI Presence Score

A 0–100 composite of how favorably AI represents you across a benchmark, written at scoring time. It folds together how prominently you appear, whether you win comparisons, whether what AI says is accurate, and how favorably you’re framed. It is a composite, not an average of the metrics below — those measure single dimensions; the score weighs all of them together.

Read the trend, not the absolute. See The AI Presence Score for how the dimensions combine and why run-to-run variance is normal.

Coverage

A categorical label on each evaluation describing how present you are in that one response. One of five values, most to least prominent:

  • Primary — you’re the main subject of the answer.
  • Substantial — you’re discussed at length, but not the sole focus.
  • Peripheral — you’re mentioned with some detail among others.
  • Incidental — a passing mention.
  • Absent — you don’t appear at all.

Coverage is per-response and categorical. It’s the raw material the visibility rate is built from — it is not itself a percentage.

Visibility rate

The share of scored evaluations where coverage is not absent — i.e. how often you show up at all. A fraction from 0 to 1, shown as a percentage.

One critical detail: your report computes visibility organic-only. Head-to-head prompts that name your company directly (e.g. “Compare X vs Y”) are excluded, because an AI mentioning you only because the question forced it to isn’t real presence. What’s left measures how often you surface when a buyer asks an open question about the category.

Win rate (W-L-T)

For head-to-head comparisons, each evaluation resolves to one outcome: a win, a loss, a tie, or not compared (the prompt wasn’t a comparison, or AI made no call). Win rate = wins ÷ decided, where decided = wins + losses + ties. Ties count in the denominator — a hedged answer is not a win.

Two rules shape this:

  • Outcomes come from AI’s actual pick in the response, extracted per feature and overall — not a holistic guess.
  • A recommendation of one of your own products over another is a brand win, not a loss. Scoring understands your product family. See Subjects.

Win rate is also available per competitor and per feature, over the same underlying outcomes.

Sentiment

How favorably you’re characterized when you do appear, aggregated to a 0–100 scale (higher is more favorable). Sentiment is measured per response and rolled up; it’s independent of coverage — you can be highly present with lukewarm sentiment, or briefly mentioned in glowing terms.

How they relate

  • Coverage feeds visibility rate — coverage is the per-response label, visibility is the fraction of responses that aren’t absent.
  • Visibility, win rate, accuracy, and sentiment are the dimensions the AI Presence Score composites into one number.
  • Every metric drills to its evidence: score → evaluations → response text → claim → cited source. See Runs and scoring.