KnitKnot

# Read your report

What the AI Presence Score means, how to read wins and losses, and how to drill from a headline number to the exact AI response behind it.

## At a glance

  1. 1. **Open a period**: Choose a scored benchmark period from Results and check its coverage.
  2. 2. **Read the answer**: Drill from a score or head-to-head outcome to the captured response.
  3. 3. **Decide what follows**: Use the claim and source evidence to choose a supported response.

Open **Benchmarks → Results** after a run is scored, then select a benchmark period. The period groups the results; **Runs** shows the batches that produced them. Read the captured answers behind a number before deciding what it means. A partial run may leave some questions or engines unmeasured.

## The AI Presence Score

The headline is a 0–100 composite of how favorably AI represents you in its answers to buyer questions: how often you show up, how you fare head-to-head, whether what AI says about you is accurate, and how you are framed. It is designed to be tracked over time; the trend across runs matters more than any single reading.

Two supporting numbers to know:

  • - **Visibility:** the share of open-question answers where you were mentioned. Questions that name you directly are excluded.
  • - **Win rate:** the share of head-to-head outcomes you won, including ties in the total. The Head-to-head tab also shows **decided win rate**, which excludes ties.

## What AI tells buyers

This section is the qualitative core: the recurring claims AI makes about your company, with the captured quotes and engines behind them. Claim conclusions use available company facts, receipts, and validation gates; missing evidence remains unverifiable rather than being treated as false.

## Competitive results

Use the period's **Head-to-head** tab to see where the answers favored you or a competitor. Open the supporting answer to read the recommendation in context. A result from one prompt and engine is evidence for that run, not a prediction of what every buyer will see.

One nuance: if AI recommends one of your own products over another, that's a win for your brand, not a loss : the scoring knows your product family.

## Sources

When a captured response exposes a reliable citation signal, KnitKnot can bind a claim to that source. Open **Intelligence → Sources** to inspect the owned, competitor, and third-party pages in captured citations. [Trace a cited source](/docs/trace-a-cited-source/) walks through the table and page detail. When no reliable signal can be bound to a claim, attribution remains empty.

## From report to action

Repeated gaps in the report can become **Issues**: persistent records such as a factual problem, missed capability, losing comparison, coverage gap, or access failure. Issues feed **Playbooks**: evidence-grounded briefs or technical fix plans your team can use to respond. After publication, a later full benchmark compares observed answer, citation, score, and issue changes without treating the intervention as the only explanation.

## Sharing

The period's **Reports** tab lists draft and published reports. A published report has a public link at your workspace's `knitknot.io` address. Follow [Share your report](/docs/share-your-report/) to create, review, and publish one.

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Read your report

What the AI Presence Score means, how to read wins and losses, and how to drill from a headline number to the exact AI response behind it.

Updated

At a glance

  1. Open a period

    Choose a scored benchmark period from Results and check its coverage.

  2. Read the answer

    Drill from a score or head-to-head outcome to the captured response.

  3. Decide what follows

    Use the claim and source evidence to choose a supported response.

Open Benchmarks → Results after a run is scored, then select a benchmark period. The period groups the results; Runs shows the batches that produced them. Read the captured answers behind a number before deciding what it means. A partial run may leave some questions or engines unmeasured.

The AI Presence Score

The headline is a 0–100 composite of how favorably AI represents you in its answers to buyer questions: how often you show up, how you fare head-to-head, whether what AI says about you is accurate, and how you are framed. It is designed to be tracked over time; the trend across runs matters more than any single reading.

Two supporting numbers to know:

  • Visibility: the share of open-question answers where you were mentioned. Questions that name you directly are excluded.
  • Win rate: the share of head-to-head outcomes you won, including ties in the total. The Head-to-head tab also shows decided win rate, which excludes ties.

What AI tells buyers

This section is the qualitative core: the recurring claims AI makes about your company, with the captured quotes and engines behind them. Claim conclusions use available company facts, receipts, and validation gates; missing evidence remains unverifiable rather than being treated as false.

Competitive results

Use the period’s Head-to-head tab to see where the answers favored you or a competitor. Open the supporting answer to read the recommendation in context. A result from one prompt and engine is evidence for that run, not a prediction of what every buyer will see.

One nuance: if AI recommends one of your own products over another, that’s a win for your brand, not a loss : the scoring knows your product family.

Sources

When a captured response exposes a reliable citation signal, KnitKnot can bind a claim to that source. Open Intelligence → Sources to inspect the owned, competitor, and third-party pages in captured citations. Trace a cited source walks through the table and page detail. When no reliable signal can be bound to a claim, attribution remains empty.

From report to action

Repeated gaps in the report can become Issues: persistent records such as a factual problem, missed capability, losing comparison, coverage gap, or access failure. Issues feed Playbooks: evidence-grounded briefs or technical fix plans your team can use to respond. After publication, a later full benchmark compares observed answer, citation, score, and issue changes without treating the intervention as the only explanation.

Sharing

The period’s Reports tab lists draft and published reports. A published report has a public link at your workspace’s knitknot.io address. Follow Share your report to create, review, and publish one.