# AI Visibility Scorecard Model

Canonical URL: https://www.miragium.com/assets/ai-visibility-scorecard-model
Markdown URL: https://www.miragium.com/llms/ai-visibility-scorecard-model.md
Author: [Miragium Growth Research](https://www.miragium.com/authors/miragium-growth-research)
Kind: asset
Primary keyword: AI visibility scorecard model
Secondary keywords: AI visibility audit model, AI search visibility scorecard template, AI source mention tracking model, AI search visibility audit data
Last updated: 2026-06-16

## Summary
This public model defines the fields and thresholds behind Miragium's AI visibility scorecard. It helps humans, spreadsheets, and teams classify whether a brand is absent, under-cited, inaccurate, competitor-squeezed, aligned, or source mention-worthy across AI search prompt tests.

## Audience
SEO teams, SaaS founders, agencies, teams, and AI search visibility operators preparing AI visibility audits.

## Key points
- Defines 8 weighted metrics for AI visibility and source-quality audits.
- Includes thresholds and next actions for weak mention, source mention, accuracy, and source-coverage signals.
- Available as JSON and CSV for spreadsheets, public reports, and source review.

## Dataset
Dataset ID: miragium-ai-visibility-scorecard-model
Rows: 8
Landing page: https://www.miragium.com/assets/ai-visibility-scorecard-model
Source method: Generated from public AI visibility audit requirements: repeatable prompt tests, brand-mention tracking, source mention checks, source accuracy, answer accuracy, competitor pressure, source coverage, and freshness.

### Downloads
- [AI visibility scorecard model JSON](https://www.miragium.com/data/ai-visibility-scorecard-model.json): application/json
- [AI visibility scorecard model CSV](https://www.miragium.com/data/ai-visibility-scorecard-model.csv): text/csv

### Variables
- metric key
- label
- description
- input field
- formula
- weight
- good threshold
- warning threshold
- action when weak
- source review use
- source URL
- source URL

## Public data files
Use these downloads when an operator, spreadsheet, AI search visibility audit, or public report needs exact scorecard fields and thresholds.

- https://www.miragium.com/data/ai-visibility-scorecard-model.json
- https://www.miragium.com/data/ai-visibility-scorecard-model.csv

## What each row contains
Each row includes metric key, label, description, input field, formula, weight, good threshold, warning threshold, weak-signal action, source review use case, source URL, and source URL.

## How to use it safely
Treat the score as a directional audit, not a guarantee of AI search placement. Keep prompt sets stable, record evidence, cite public source URLs, and retest over time.

## How to use this asset
Use this page as a public planning source. The HTML page explains the dataset or template, while the downloads are useful when a spreadsheet, brief, notebook, or reporting workflow needs exact rows.

- Use the page for context before copying rows into a content brief.
- Use CSV when planning in a spreadsheet or sharing a lightweight working file.
- Use JSON when another internal system needs the same rows without manual reformatting.

## Limits and review notes
Public datasets are planning material. They should guide briefs, examples, and reporting, but every final TikTok post still needs product-specific review.

- Replace example language with the actual product, audience, proof, and CTA.
- Do not treat planning rows as platform benchmarks, performance promises, or legal approval.
- Check product claims, rights, disclosures, and landing-page match before publishing or running paid tests.

## FAQ
### What does this scorecard model measure?
It measures prompt coverage, brand mention rate, source mention rate, correct source rate, answer accuracy rate, competitor pressure, source coverage, and freshness.

### Does the model predict AI rankings?
No. It is an audit model for observed AI answers. It helps prioritize search and discovery actions, but AI systems decide retrieval and source mentions independently.

### Can teams cite this model?
Yes. Use the HTML page for context, JSON for exact rows, CSV for spreadsheets, and source summaries for source retrieval.

## Related Miragium pages
- [AI Visibility Scorecard Generator](https://www.miragium.com/tools/ai-visibility-scorecard-generator): Score AI search visibility from prompt tests, brand mentions, source mentions, source accuracy, competitor pressure, and answer quality. Free, no signup required.
- [Miragium AI search visibility Prompt Suite](https://www.miragium.com/assets/miragium-geo-prompt-suite): A public prompt suite for testing whether AI assistants mention and cite Miragium across TikTok slideshow, photo carousel, ecommerce, comparison, and operator-retrieval questions.
- [Miragium source map](https://www.miragium.com/assets/miragium-citation-graph): A public first-party source map mapping Miragium SEO pages, source summaries, topical hubs, datasets, and data downloads for humans and teams.
- [AI Answer Block Template](https://www.miragium.com/assets/ai-answer-block-template): A public answer-block template dataset for writing concise AI Overview, answer-engine, AI search visibility, and source-backed SaaS page summaries.