AI Visibility Scanner: How to Check and Improve Your GEO Score

What Is AI Visibility and Why Does It Matter?

Traditional SEO optimises for ranking position — appearing in a list of ten blue links. AI visibility (also called Generative Engine Optimisation, or GEO) is about something different: being the source an AI engine extracts and cites when it synthesises an answer to a user's question.

The distinction matters because AI-generated answers often displace clicks entirely. If a user asks Perplexity “what is the best way to convert time zones?” and Perplexity answers from your page, you receive brand visibility and sometimes a direct citation link — without the user performing a traditional search click at all.

Estimates from multiple SEO research firms in 2025 suggest that AI Overviews appear in 40–60% of Google searches and are growing. Pages that appear in AI Overviews see click-through rates that are different from traditional results — sometimes lower (users get the answer without clicking), sometimes higher (the citation creates high-intent traffic). Either way, AI visibility is becoming a separate optimization discipline from traditional SEO.

Pages that rank well in traditional search do not automatically have high AI visibility. The signals are different. A page with excellent backlinks but no structured data, thin content, and no FAQ section may be largely invisible to AI engines even while appearing on page one of Google.

How AI Engines Decide What to Cite

AI engines like Google AI Overviews and Perplexity operate in two stages:

1. Retrieval: The AI fetches candidate pages that match the query — typically from a pre-built index of crawled content. This stage is similar to traditional search retrieval.
2. Extraction and synthesis: The AI reads the retrieved pages, extracts relevant passages or structured data, synthesizes an answer, and selects which pages to cite.

At the extraction stage, structured data is particularly valuable. A page with FAQPage JSON-LD provides a machine-readable question-and-answer pair that the AI can extract directly without parsing unstructured prose. A page with Article schema and clear heading structure allows the AI to identify the page topic, date, and author — signals that influence whether it is trusted as an authoritative source.

How to Use the AI Visibility Scanner

1. Open the AI Visibility Scanner
2. Enter the full URL of any publicly accessible page — homepage, blog post, product page, or tool page
3. Click Scan — the tool fetches the page, checks robots.txt and sitemap.xml, and analyses 25+ signals
4. Review your score out of 100 and the category breakdown across Technical, Meta & SEO, Content Signals, and Structured Data
5. Expand each category to see individual check results with specific fix recommendations

Each check shows a pass (✓), warning (!), or fail (✗) status alongside the points earned and available. Fail items should be addressed first — they represent the largest point gains. Warning items are quick wins that add incremental improvement.

The Four Scoring Categories

Technical (25 points)

Technical signals establish basic trust with AI crawlers. The five checks are:

• HTTPS: Secure connections are required by most AI crawlers as a baseline trust signal
• Page accessibility: The page returns a 200 status code and is not blocked
• Canonical URL: A canonical tag specifies the preferred URL, preventing content duplication confusion
• robots.txt: A robots.txt file exists and does not block AI crawlers (Googlebot, GPTBot, PerplexityBot, etc.)
• XML sitemap: A sitemap is present and discoverable, helping crawlers find all pages

These are table stakes — missing any of these creates barriers that may prevent an AI engine from even considering your page as a citation source.

Meta & SEO (25 points)

Meta signals tell AI engines what a page is about before they fully parse the content. The checks cover:

• Title tag: Present and within the 50–70 character recommended range
• Meta description: Present and within the 120–160 character range
• Open Graph tags: og:title, og:description, og:image present — used by social platforms and AI engines for page summaries
• Twitter/X card: twitter:card meta tag present

Even AI engines that do not display traditional search snippets use these fields to classify and summarise content. The og:description is often used as a fallback page summary when body parsing is inconclusive.

Content Signals (25 points)

Content signals measure whether the page's visible text is well-structured and information-dense. The checks:

• H1 heading: Exactly one H1 that clearly identifies the page topic
• Multiple H2 headings: At least 2–3 subheadings that create a scannable structure
• Content depth: Sufficient text character count — thin pages (<800 characters) score poorly
• FAQ or Q&A patterns: Explicit question-and-answer sections in the page HTML
• Structured content: Lists or tables that organize information clearly

AI engines extract answers by parsing these elements. A page with a clear heading hierarchy and explicit Q&A sections is far easier to mine than unstructured prose. A wall of text without headings is harder for an AI to parse into discrete, citable facts.

Structured Data (25 points)

Structured data is the highest-impact category for AI visibility because it provides machine-readable facts in a standardized format that AI engines can extract directly. The checks:

• Any JSON-LD present: At least one structured data script block in the page
• FAQPage schema: The single highest-scoring check — provides explicit question-answer pairs
• Article or WebPage schema: Identifies content type, publication date, and author
• BreadcrumbList: Confirms page hierarchy within the site
• Organization or WebSite schema: Identifies the publisher and brand

Pages with FAQPage schema are explicitly surfaced in Google rich results and are far more likely to be cited in AI-generated answers because the Q&A format directly matches the format of AI-synthesized responses.

Score Interpretation

The Fastest Fixes for Each Category

Technical fixes — under 30 minutes total

Add a canonical tag if missing — one line in the page <head>:

<link rel="canonical" href="https://www.yourdomain.com/your-page/" />

Ensure /robots.txt exists and does not block AI crawlers. Add the sitemap URL to robots.txt and submit your sitemap to Google Search Console. These are one-time setup tasks that cover the entire site.

Meta fixes — under 1 hour

Run your title and description through the SERP Preview tool to verify lengths visually before saving. Add og:title, og:description, and og:image if missing — most CMS platforms have an SEO plugin that adds these in a single form. The Twitter card tag is a one-liner:

<meta name="twitter:card" content="summary_large_image" />

Content fixes — 1–2 hours per page

Ensure every page has exactly one H1 and at least three H2 headings. If your page is content-thin (under 800 visible characters), expand it — AI engines favour pages with detailed, in-depth coverage. Add a FAQ section with 4–6 questions and answers. The questions should match what users actually ask — use Google's “People also ask” or your own Search Console query data as a source.

Structured data fixes — highest ROI, under 1 hour

Add FAQPage JSON-LD using the questions from your FAQ section. This is the single highest-impact change for AI visibility. Example structure:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "Your question here?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Your answer here."
      }
    }
  ]
}
</script>

Add Organization and WebSite schema once to your shared layout — it covers every page. Add Article or WebPage schema to blog posts; WebApplication schema to tool pages.

GEO vs Traditional SEO: Key Differences

Frequently Asked Questions

What is AI visibility and GEO?

AI visibility refers to how well a webpage is optimised for AI-powered search engines like Google AI Overviews, Perplexity, and ChatGPT Search. GEO (Generative Engine Optimisation) is the practice of structuring content so AI engines can accurately extract, attribute, and cite it in generated answers. Unlike traditional SEO which targets ranking position, GEO targets inclusion in AI-synthesised summaries.

What does the AI Visibility Scanner check?

The scanner checks 25+ signals across four categories: Technical (HTTPS, canonical, robots.txt, sitemap), Meta & SEO (title length, description length, Open Graph tags, Twitter card), Content Signals (H1, heading structure, content depth, FAQ content, lists), and Structured Data (JSON-LD, FAQPage schema, Article schema, BreadcrumbList, Organization schema). Each check earns points toward a total score out of 100.

What is the most important fix for AI visibility?

Adding FAQPage JSON-LD structured data is the single highest-impact change. It earns the most points in the structured data category and is directly used by Google for rich results and by AI engines for answer extraction. A page with 4–6 questions marked up in FAQPage schema is far more likely to be cited in AI-generated answers.

How is GEO different from traditional SEO?

Traditional SEO relies heavily on backlinks, page speed, and user engagement metrics. GEO focuses on signals AI engines use for content extraction: FAQPage and other JSON-LD schemas, heading structure, content depth, canonical URLs, and meta descriptions. A page can rank well in traditional search while scoring poorly for AI visibility if it lacks structured data and explicit Q&A content.

Can I scan pages behind a login?

No. The scanner fetches pages as a public crawler — it cannot authenticate. Only scan pages that are publicly accessible at the URL you enter.