Overview
Cited tracks multiple metrics to give you a complete picture of your AI search visibility. This guide explains what each score measures, how it's calculated at a high level, and what targets you should aim for.
AI Visibility Score
What it measures: Your overall visibility across AI search engines, expressed as a single number from 0 to 100.
The AI Visibility Score is a composite metric that combines signals from your audit results and health metrics. It answers the question: "If someone asks an AI about my industry, how likely am I to appear in the response?"
How It's Calculated
The score aggregates multiple factors:
- How frequently your brand is cited across AI providers
- The quality and prominence of those citations
- Your share of voice relative to competitors
- The health and readiness of your website for AI consumption
Each factor is weighted based on its impact on real-world AI citation behavior. The score updates every time you run a new audit, allowing you to track progress over time.
What Good Looks Like
| Score Range | Rating | Meaning |
|---|---|---|
| 80-100 | Excellent | Your brand is consistently cited across AI platforms. You're a recognized authority. |
| 60-79 | Good | You appear regularly but have room to improve prominence and coverage. |
| 40-59 | Fair | You show up occasionally. There are clear gaps in your AI visibility strategy. |
| 20-39 | Poor | AI search engines rarely mention you. Significant work is needed. |
| 0-19 | Critical | You're effectively invisible to AI search. Immediate action is required. |
Most businesses score between 15 and 45 on their first audit. Don't be discouraged by a low initial score — it establishes your baseline and makes your improvement measurable.
Cited KPI
What it measures: The percentage of AI responses that directly cite your domain or brand.
This is your most concrete metric. If you run an audit with 20 questions across 3 providers (60 total responses), and your brand appears in 12 of them, your Cited KPI is 20%.
How It's Calculated
Cited KPI = (Number of responses citing your brand / Total number of responses) x 100
A "citation" counts when the AI response either:
- Mentions your brand by name in a relevant context
- Links to or references your domain as a source
- Recommends your product or service by name
What Good Looks Like
- Above 40% — Strong. You're a go-to source in your space.
- 20-40% — Solid foundation. Focus on expanding into the question categories where you're missing.
- 10-20% — Emerging presence. Target quick wins in content quality and structured data.
- Below 10% — Early stage. Prioritize foundational work: authoritative content, schema markup, and third-party presence.
Share of Voice
What it measures: How often your brand appears in AI responses compared to your competitors.
Share of Voice puts your visibility in competitive context. If AI responses in your space mention five brands and yours is cited as often as the top competitor, you have a strong share of voice. If competitors dominate and you rarely appear, your share is low.
How It's Calculated
Cited tracks every brand and domain mentioned in audit responses. Your Share of Voice is the percentage of total competitor mentions that belong to your brand.
For example, if across all audit responses there are 50 total brand mentions in your category and your brand accounts for 15 of them, your Share of Voice is 30%.
What Good Looks Like
Share of Voice is inherently relative — a "good" number depends on how many competitors are in your space.
- Market leader: 30%+ in a crowded market, 50%+ in a niche market
- Competitive: 15-30% — you're in the conversation consistently
- Emerging: 5-15% — you appear but aren't a primary reference
- Invisible: Below 5% — competitors own the AI conversation in your space
Track this metric over time. Even a 5% improvement in Share of Voice can translate into meaningful increases in brand awareness and referral traffic from AI-assisted searches.
Health Metrics
Health Metrics measure the readiness of your website to be discovered and cited by AI. Unlike the audit-based metrics above, these come from Cited's scan of your website's content and technical infrastructure.
Content Quality
What it measures: How well your content is structured, written, and organized for AI comprehension.
AI models prefer content that is clearly structured with headings, uses definitive and quotable statements, includes supporting evidence, and covers topics comprehensively. Content Quality evaluates your pages against these criteria.
Target: 70+. Scores below 50 indicate content that may be difficult for AI models to parse or extract useful information from. Focus on clear structure, authoritative language, and comprehensive topic coverage.
Crawl Coverage
What it measures: How accessible your site is to AI crawlers and indexing systems.
If AI engines can't reach your content, they can't cite it. Crawl Coverage checks whether your pages are accessible, whether your robots.txt and meta tags allow AI crawlers, and whether your site structure supports efficient crawling.
Target: 85+. This is a foundational metric. If Crawl Coverage is low, other improvements will have limited impact. Common issues include restrictive robots.txt rules, broken internal links, and pages blocked by authentication or JavaScript rendering.
Trust Score
What it measures: The presence of trust signals that AI models use when deciding which sources to cite.
Trust signals include clear authorship attribution, references to external sources, publication dates, editorial standards, and domain authority indicators. AI models are more likely to cite sources they perceive as trustworthy and authoritative.
Target: 65+. Improving Trust Score often involves adding author bios, citing primary sources in your content, maintaining consistent publication schedules, and building backlinks from reputable domains.
Schema Completeness
What it measures: How thoroughly your site uses structured data (Schema.org markup) to help AI understand your content.
Schema markup provides explicit, machine-readable context about your content — what type of content it is, who wrote it, what organization it belongs to, and how it relates to other entities. AI models use this structured data to build more confident citations.
Target: 75+. Key schema types to implement include Organization, Article, FAQPage, Product, and BreadcrumbList. Even basic schema markup gives you an advantage over competitors who have none.
AI Readiness
What it measures: An overall assessment of how prepared your site is to perform in AI search.
AI Readiness combines elements from the other health metrics with additional checks specific to AI discovery: presence of an llms.txt file, content format compatibility, entity clarity, and topical authority signals.
Target: 70+. This is a composite health metric. Improving the individual metrics above will naturally raise your AI Readiness score.
Using Your Scores Effectively
Scores are most valuable as directional guides, not absolute judgments. Use them to:
- Establish a baseline. Your first audit creates a starting point. Every future audit measures progress against it.
- Prioritize work. Low scores in specific areas tell you where to focus. A high Content Quality score but low Schema Completeness score means you should prioritize structured data, not content rewrites.
- Track progress. Run audits regularly — monthly at minimum — to see how your improvements translate into better AI visibility.
- Compare against competitors. Share of Voice and Cited KPI show you where you stand relative to the competition, not just against an abstract benchmark.
For guidance on turning your scores into concrete actions, read Your First Action Plan.