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AEO audit · Aug 8, 2026

example.com

on the querywhat is example domain
26AEO score
Currently uncited
Not cited at top 0·simulated retrieval against 0 candidates
⚡ This Week — top 5 fixes📈 Predict score⬇ CSV⬇ JSON View page

The 30-signal rubric

10 ok · 10 weak · 27 absent

Every signal is measurable from your page. Hover for the detail and a remedy.

Structure

29/100
JSON-LD structured data0
No JSON-LD blocks found. Answer engines key off schema.org markup to ground citations.
Fix: Add at least one schema.org JSON-LD block — Article, Product, FAQPage, or HowTo are the highest-lift types.
JSON-LD validity100
No JSON-LD blocks to validate (the presence signal covers that).
Schema type matches query intent0
No schema types — for a informational query, add one of: Article, BlogPosting, FAQPage, HowTo.
Fix: Add a Article JSON-LD block — the highest-leverage schema type for a "what is example domain" query.
FAQ / Q&A schema0
No FAQPage / QAPage schema — AI Overviews preferentially cite pages exposing structured Q&A.
Fix: Add a FAQPage schema with 3-5 questions buyers actually ask. The single most direct path to AI Overview citation.
H1 quality60
H1: "Example Domain" (14 chars).
Fix: Adjust H1 length to 20-80 chars — shorter than 20 lacks context, longer than 80 loses retrieval focus.
H2 subtopic coverage0
0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.
Fix: Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.
Lists (bulleted / numbered)0
No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly.
Fix: Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.
Comparison tables50
No tables. Comparison / specification tables are heavily cited for product and technical queries.
Image alt-text coverage100
No images — alt-text coverage trivially complete.
Open Graph metadata0
Open Graph: title ✗, desc ✗, image ✗.
Fix: Add og:title, og:description, og:image meta tags. AI engines use OG for the cited preview card.
Internal linking quality0
0 internal links (0 with descriptive anchors), 1 external.
Fix: Add 5-15 internal links to related pages on the same domain — engines use the internal link graph to weight topical relevance.
Page weight + render-blocking100
1 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 0/0 images without lazy-load.
GEO-SFE structural depth (macro/meso/micro)28
Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 2.0 chunks/section avg. Micro: 0.00% visual emphasis.
Fix: Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.

Authority

14/100
Outbound links to authoritative sources0
0 links to authoritative domains (.edu, .gov, named sources).
Fix: Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.
Inline citations and attributions0
0 bracketed citations + 0 attribution phrases (per 200 words: 0%).
Fix: Add inline citations ([1], [2]) or attribution phrases ("according to X"). GEO factor #1 for credibility-weighted citation.
Statistic density0
0 numerical facts (~0 per 100 words).
Fix: Add concrete statistics with sources. AI engines preferentially cite paragraphs containing numbers — a GEO paper §4.1 finding.
Expert quotations0
0 blockquotes + 0 long inline quotes.
Fix: Include at least one direct quote from a named expert, ideally in a <blockquote>. Quote-rich pages are 28% more likely to be cited (GEO paper).
Author byline0
No author byline. E-E-A-T penalises anonymous content.
Fix: Add a visible author byline (a `<div class="byline">` or `[rel="author"]`) AND a `<meta name="author">` tag.
Publish + update date markup0
No structured publish date. Freshness ranking can't be applied.
Fix: Add `<time datetime="...">` for published date AND a `<meta property="article:modified_time">` for updates.
Content freshness0
No parseable date — engines treat undated content as stale.
Fix: Add a parseable date — `<time datetime="2026-01-15">` or `<meta property="article:modified_time">`.
Technical / domain vocabulary100
5 multi-syllable words (~29.4% of total).

Content

34/100
Direct answer in the lead50
2 of 4 query terms appear in the first paragraph.
Fix: Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.
Query-term coverage75
75% of query terms appear somewhere on the page.
Named-entity coverage30
3 distinct proper-noun entities mentioned.
Fix: Mention the named entities (people, products, organisations, places) the buyer query implies. Entity coverage feeds knowledge-graph retrieval.
Readability (Flesch Reading Ease)20
Reading-ease score: 21.9 (target 60-70).
Fix: Page reads too academic — shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3).
Content depth0
17 words. Target 300-2500 — engines bias toward focused depth.
Fix: Page is too short. Expand to at least 500 words covering the query in depth.
Information density30
Unique-word ratio: 88.2% (target 40-60%).
Fix: Vocabulary varies too wildly — content may lack topical focus. Engines prefer focused pages.
Definitional sentences0
0 definitional sentences.
Fix: Include definitional sentences ("X is...", "X refers to..."). Engines specifically extract definitions for AI Overview snippets.
BLUF — answer in first 100 words65
First 100 words cover 2/4 query terms + definitional phrase ✓.
Fix: Put the answer in the FIRST 100 words — Perplexity's pipeline summarizes that exact span before reranking. "BLUF" (bottom-line-up-front) is the format that wins.
Mega-page coverage (what/who/how/pricing)0
0/4 facets covered (what ✗, who ✗, how ✗, pricing ✗).
Fix: Cover what / who / how / pricing in the same URL. Chatoptic's 75k-page study found the top 4.8% of repeatedly-cited pages share this single-URL completeness.
YouTube video presence0
No YouTube presence.
Fix: Embed (or link to) a YouTube video covering this topic. Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews.
Sub-query coverage67
2/3 decomposed sub-questions addressed on the page.
Fix: Cover the sub-questions buyers actually ask along with the seed query. Currently failing on: how does what is example domain work

Trust

43/100
HTTPS100
Page served over HTTPS.
Canonical URL0
No canonical link element.
Fix: Add `<link rel="canonical" href="...">`. Engines use it to de-duplicate competing URLs for the same content.
Mobile-friendly viewport100
Viewport meta tag present.
Twitter Card30
No Twitter Card — secondary signal but easy to add.
Fix: Add `<meta name="twitter:card" content="summary_large_image">` and the matching title/description/image.
Meta description0
No meta description.
Fix: Add a `<meta name="description">` summarising the page in 120-160 characters.
AI retrieval-bot access (robots.txt)70
No robots.txt found — all crawlers default to allowed (acceptable for AEO).
llms.txt present at /llms.txt0
No /llms.txt found. Adoption is ~10% in 2026; presence is a recognized AI-readiness signal.
Fix: Add a spec-compliant /llms.txt at the site root. Use VectorCite's generator at /audit/llms-txt — free, no signup. Anthropic's Claude and the major IDE coding agents fetch it for retrieval.

E-E-A-T

17/100
First-person language0
0 first-person pronouns (0.0% of words). Target 0.5-3%.
Fix: Add first-person language showing lived experience — "we", "our team", "I". Google rates first-person as direct evidence of the new E-for-Experience EEAT pillar.
Case study / concrete examples0
0 case-study patterns matched (examples, results, hands-on phrases).
Fix: Add at least 2-3 concrete examples or mini-case-studies. "We helped X achieve Y" beats abstract claims; AI engines preferentially cite pages with measurable outcomes.
Author bio with credentials0
No `.author-bio` / `[itemprop="author"]` element found.
Fix: Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).
Byline depth (link + reviewer + date)0
no linked byline, no reviewer, no date
Fix: Strengthen the byline: link author name to an author profile page; add "reviewed by" / "edited by" markup; mark published + modified dates explicitly.
Brand recognized as Wikidata entity100
Wikidata: Q114424786 — mathematical subtext, which presents an application or an illustration of the subject or of the theo
Press / media mentions0
0 press-mention pattern(s) matched.
Fix: Add a "Featured in" / "As seen in" strip listing publications that have covered you. External recognition is a top authority signal.
Privacy + Terms links0
Privacy ✗, Terms ✗.
Fix: Add Privacy Policy and Terms of Service links (typically in the footer). Their absence is a hard trust-floor signal — Google's quality raters down-rank pages that lack them.
Contact information0
email ✗, phone ✗, address ✗, no contact link
Fix: Expose verifiable contact info: an email link, a phone number, and ideally a physical address marked up with `<address>` or `itemprop="address"`. Anonymous sites read as low-trust.

The Fix Kit

Currently uncited (26/100) — 14 foundational patches required

Ready-to-paste patches. Schema.org JSON-LD, meta tags, copy guidance. The first three below are unlocked; the rest are gated behind a free account.

Article JSON-LD

A Article schema is the strongest single AEO signal for a informational query. Paste this in the <head>.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Example Domain",
  "description": "Example Domain",
  "url": "https://example.com",
  "datePublished": "2026-08-08",
  "author": {
    "@type": "Person",
    "name": "Add author name"
  },
  "publisher": {
    "@type": "Organization",
    "name": "Example",
    "logo": {
      "@type": "ImageObject",
      "url": "https://example.com/logo.png"
    }
  }
}
</script>

FAQPage JSON-LD

FAQPage is the single most-cited schema type by Google AI Overviews. Add 3-5 Q&A pairs covering what buyers ask.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is .xxx?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": ".xxx is a sponsored top-level domain (sTLD) intended as a voluntary option for pornographic websites on the Internet. This option enables website operators to establish a web address like example.xxx instead of example.com. The sponsoring organization is the International Foundat"
      }
    },
    {
      "@type": "Question",
      "name": "Why does .xxx matter?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "A 1-2 sentence explanation of the practical value or impact."
      }
    }
  ]
}
</script>

Organization JSON-LD

Organization schema gives the engine an E-E-A-T anchor — pages without one are treated as anonymous.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Example",
  "url": "https://example.com",
  "logo": "https://example.com/logo.png",
  "sameAs": [
    "https://twitter.com/your-handle",
    "https://linkedin.com/company/your-org"
  ]
}
</script>
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