AI Visibility Score: What It Is, How It's Calculated, and How to Improve It

Your AI visibility score is a measure of how likely ChatGPT, Perplexity and other AI search engines are to cite your website when answering a user's question. Most websites score poorly - and do not know it.

What an AI visibility score measures

An AI visibility score is a composite metric that measures how well-positioned your website is to be cited as a source by AI-powered search engines. These include ChatGPT (with Browse), Perplexity AI, Google AI Overviews, Microsoft Copilot and similar platforms that synthesise answers from web content.

Unlike traditional SEO metrics - domain authority, page rank, keyword positions - an AI visibility score focuses specifically on the signals that determine whether an AI engine will choose to cite your website. It answers the question: if a user asks a question that your website should answer, how likely is an AI engine to include you in its response?

The score is expressed as a number from 0 to 100. It is calculated by auditing your website across seven distinct categories, each weighted by its impact on actual AI citation behaviour. The result is a single number you can track over time, alongside a detailed breakdown showing exactly where to focus your efforts.

The 8 scoring categories explained

The SearchScore AI visibility scoring model covers seven distinct categories. Each reflects a different dimension of AI search visibility, and each carries a different weight in the final score.

1. AI Citability (25%)

This is the most heavily weighted category because it governs the most fundamental question: can AI engines actually access and read your website? AI Citability covers three main areas.

First, crawler access: does your robots.txt file allow or block AI crawlers such as GPTBot (ChatGPT), ClaudeBot (Anthropic), PerplexityBot (Perplexity) and Bingbot (Microsoft Copilot)? A surprising number of websites block one or more of these bots - sometimes deliberately, sometimes accidentally through overly broad wildcard rules.

Second, llms.txt: have you published this file? Similar to robots.txt but specifically for large language models, llms.txt tells AI systems which of your pages are most important and provides the context they need to represent your content accurately. It is still an emerging standard, but adoption is growing rapidly.

Third, content structure: is your content structured in a way that AI crawlers can parse? Pages that rely heavily on JavaScript rendering, that hide key content behind interactions, or that use iframes for primary content score lower on citability.

2. E-E-A-T Content (20%)

Experience, Expertise, Authoritativeness and Trustworthiness - borrowed from Google's search quality guidelines - carries significant weight in AI citation decisions. AI models have been trained to identify and prefer content that demonstrates real-world expertise.

This category evaluates: the presence of named authors with credentials, the quality and depth of content (not just length), whether your claims are supported by data or citations, the use of original research or primary sources, and clear indicators of editorial standards. A faceless website with anonymous, thin content scores poorly here regardless of its traffic.

3. Brand Authority (15%)

AI engines are more likely to cite brands they recognise as legitimate and established. Brand Authority measures how well your brand is represented across the wider web - not just your own website.

Signals include: consistent business information (name, address, phone) across directories, mentions in third-party publications, presence on knowledge platforms such as Wikidata or Crunchbase, social proof indicators, and the overall footprint of your brand across the internet. A brand that exists only on its own domain is harder for AI to verify and cite with confidence.

4. Technical Health (10%)

Technical factors affect both the ability of AI crawlers to access your site and the trust signals your site sends to AI models. This category covers page load speed (AI crawlers have timeout limits just like regular bots), HTTPS security, Core Web Vitals, mobile responsiveness, and the semantic quality of your HTML markup.

Clean, well-structured HTML with proper heading hierarchies, descriptive alt text and semantic element usage makes it significantly easier for AI engines to extract and understand your content.

5. Structured Data (10%)

Schema.org markup is one of the clearest signals you can give to AI engines about what your content means. Without it, AI models must infer the meaning of your content from context alone. With it, you are explicitly telling them: "this is an article by this author," "this is a business with these details," "this is a question with this answer."

The most impactful schema types for AI visibility are Organisation, Article, FAQPage, Person and BreadcrumbList. This category audits whether you are using the right schema types, whether the markup is valid, and whether it is comprehensive enough to give AI engines the context they need.

6. Platform Optimisation (8%)

This category covers the web metadata fundamentals: Open Graph and Twitter Card tags for social sharing and AI ingestion, canonical URLs to avoid duplicate content confusion, RSS feed presence, video content and the presence of a well-structured sitemap. These are table-stakes hygiene signals that most sites should be able to pass.

7. Topical Authority (4%)

AI engines have a strong preference for citing recognised authorities on a given topic rather than generalist websites that happen to cover it. Topical Authority measures the depth and consistency of your content on your core subjects -- content hub structure, blog coverage, FAQ sections and semantic breadth.

8. AI Platform Readiness (12%)

This is the newest and most differentiating category. It measures per-engine AI search readiness -- not just whether AI crawlers can access your site, but whether each specific platform can understand and cite you.

Signals include: BingBot access and Bing Webmaster verification (Bing Copilot), Perplexity bot permissions, Google AI Overviews schema fit (FAQPage, HowTo, Speakable), answer-first content structure, OAI-SearchBot access (ChatGPT Search) and IndexNow implementation for faster AI crawl discovery. This is the category where most sites have the most room to improve -- and where early movers gain a significant edge.

What a good AI visibility score looks like

Scores are divided into five performance tiers:

Most websites we audit score between 30 and 55. The average score across our dataset sits below 45. Reaching the Strong tier (70+) puts a website ahead of the vast majority of its competitors for AI search visibility.

Quick wins to improve your score

Some improvements deliver outsized results for the effort involved. If you are starting from a low score, these are the changes to prioritise first:

1. Unblock AI crawlers in robots.txt

Check your robots.txt file for blocks on GPTBot, ClaudeBot, PerplexityBot and similar. If you find them, remove the blocks. This single change can unlock significant AI Citability points and make all other optimisations worthwhile. Without crawler access, nothing else matters.

2. Add an llms.txt file

Create a simple plain text file at yourdomain.com/llms.txt. Include a brief description of your business and a list of your most important pages with one-line summaries of each. This takes under an hour and immediately signals to AI platforms that your site is structured for AI consumption.

3. Add Organisation schema to your homepage

A properly implemented Organisation schema - with your legal name, URL, logo, contact details and social profiles - helps AI engines verify that you are a real, established entity. This has a direct positive effect on Brand Authority scoring and boosts the likelihood of being cited as a trustworthy source.

4. Add FAQPage schema to key pages

FAQPage schema puts your answers directly in front of AI engines in a format they are built to consume. Identify the three to five questions your audience most commonly asks about your product or service, create a dedicated FAQ section on your key pages, and mark it up with FAQPage schema. This is one of the fastest ways to improve AI citation frequency for specific queries.

5. Verify your Open Graph metadata

Ensure every key page has accurate og:title, og:description and og:image tags. These are used by multiple AI platforms when referencing your content and help ensure your site is represented accurately and attractively when cited.

Longer-term improvements

The quick wins above can move your score meaningfully within days. The following improvements take more sustained effort but build lasting AI search authority:

Build your brand footprint

Get listed in reputable industry directories and relevant data sources. Pursue editorial mentions in third-party publications. Ensure your business appears consistently across the web with the same name, address and description. Over time, a wider brand footprint increases the likelihood that AI models have encountered your brand in training data and live browsing.

Invest in topical depth

Choose two or three core topics that are central to your business and build genuine authority in them. Publish original research, case studies, detailed guides and expert commentary. Link between related pieces. The goal is to become the go-to source on a topic, not merely a site that mentions it.

Add author expertise signals

Add named author pages with real credentials to your key content. Link to your authors' other work, professional profiles and external publications. AI engines reward content from demonstrably expert individuals over anonymous corporate publishing.

Strengthen your structured data

Progress beyond basic Organisation and Article schema to more specific types relevant to your business. A software company benefits from SoftwareApplication and Product schema. A local business benefits from LocalBusiness schema. An event organiser benefits from Event schema. The more precisely your schema describes your content, the more accurately AI engines can represent you.

Monitor and iterate

AI search is evolving quickly. Check your AI visibility score regularly to track progress and catch any new issues. Manually test your presence in ChatGPT and Perplexity for your core queries on a monthly basis. Treat AI visibility as an ongoing programme, not a one-time fix.

Frequently asked questions

What is an AI visibility score?

An AI visibility score is a numerical measure of how likely your website is to be cited or recommended by AI-powered search engines such as ChatGPT, Perplexity and Google AI Overviews. It is calculated across multiple categories including how accessible your site is to AI crawlers, your brand authority, the quality of your structured data, your E-E-A-T signals and your technical health.

What is a good AI visibility score?

Scores above 70/100 are considered strong. Scores of 85 and above indicate AI-Ready status - the level at which websites are consistently cited in AI search results. The majority of websites score below 40, meaning most businesses have significant untapped AI search visibility.

How can I check my AI visibility score?

You can check your AI visibility score for free at SearchScore (searchscore.io). Enter your website URL and receive a full breakdown across all eight scoring categories, with a prioritised list of fixes.

Which category has the biggest impact on my AI visibility score?

AI Citability carries the most weight at 25% of the overall score. This covers whether AI crawlers can access your site, whether you have an llms.txt file, and whether your content is structured for AI consumption. E-E-A-T content is the second largest category at 20%, followed by Brand Authority at 15%.