Scoring Methodology
How the AEO Site Rank and rank are calculated - the formula, the weights, benchmarks, and what each point means.
AEO Site Rank: How Benchmarks and Peer Comparison Work
Your AEO rank is your position among all audited domains, sorted by best score. We also rank you...
Read guide →AEO Site Rank: How We Calculate Your 0-100 Rating
Your AEO Site Rank is a deterministic 0-100 score built from 48 criteria across five pillars: Answer Readiness...
Read guide →AEO Page Rank: How Individual Pages Are Scored for Citation Readiness
AEO Page Rank is a 0-100 score measuring whether a specific page is structured for AI citation. It...
Read guide →AEO Scoring Criteria
The 48 criteria that determine your AEO Site Rank.
Q&A Content Format: Write Like AI Reads
Use question-format headings (H2/H3) that mirror how real people ask AI assistants. Lead with a direct 1-2 sentence...
Read guide →FAQ Sections: 87 Questions Turned Our Score Into 88
Build a dedicated FAQ with 20+ real questions, detailed answers, and FAQPage JSON-LD schema. Use native HTML <details>/<summary>...
Read guide →Original Data: The Content AI Can't Find Anywhere Else
Publish proprietary data, first-hand analysis, and expert opinions that only you can produce. In our audits, sites with...
Read guide →Schema Coverage Ratio
Schema coverage ratio is the percentage of your indexed pages carrying relevant JSON-LD markup. Above 80% means you're...
Read guide →Canonical URL Strategy
The canonical audit checks every page for a rel="canonical" link pointing to the correct authoritative URL. Missing canonicals...
Read guide →Content Licensing Signals
The licensing audit checks for CreativeWork license properties in JSON-LD, meta tags indicating reuse policy, and copyright notices....
Read guide →Table & List Extractability
Table and list extractability measures whether your structured content uses semantic HTML -tables with thead/tbody/th, lists with ol/ul/li....
Read guide →Schema.org JSON-LD: The Scoreboard AI Actually Reads
Add JSON-LD script blocks to your pages with Schema.org types -Organization, FAQPage, Article, BreadcrumbList. In our audits, sites...
Read guide →Clean HTML: If Crawlers Can't See It, It Doesn't Exist
Your content must be in the raw HTML the server sends -not loaded by JavaScript after render. AI...
Read guide →Semantic HTML5: The Difference Between a Page and a Page AI Can Parse
Use semantic HTML5 elements: <main>, <article>, <section>, <nav>, <header>, <footer>, <time>, and <figure>. Maintain one H1 per page...
Read guide →Direct Answer Paragraphs: The First Sentence AI Steals
The first 1-2 sentences after every heading should directly answer the question that heading implies. AI engines extract...
Read guide →Sitemap Completeness
Sitemap completeness compares the URLs in your sitemap.xml against actual pages found by crawling. Missing URLs, stale lastmod...
Read guide →llms.txt -The File That Separates 63 from 34
llms.txt is a plain-text file at your domain root that hands AI assistants a cheat sheet about your...
Read guide →robots.txt for AI: Rolling Out the Red Carpet (or Slamming the Door)
Add explicit Allow rules in your robots.txt for AI crawlers: GPTBot, ClaudeBot, PerplexityBot, and Google-Extended. Without these rules,...
Read guide →Internal Linking: The Web AI Uses to Map Your Expertise
Link your pages to each other strategically with topic hubs, "Related Articles" sections, breadcrumb navigation, and cross-references between...
Read guide →Content Freshness Signals
Content freshness measures whether pages include datePublished and dateModified in both JSON-LD and HTML time elements. Pages without...
Read guide →RSS Feed Presence & Quality
An RSS 2.0 or Atom feed at a discoverable URL lets AI indexing systems detect new and updated...
Read guide →Entity Authority: Why AI Cites Some Sites and Ignores Others
Make your business a verifiable entity with Organization schema, visible contact info, named authors with credentials, and sameAs...
Read guide →Author & Expert Schema: The Byline AI Actually Checks
Add Person schema with name, jobTitle, sameAs links, and knowsAbout for every content author. Include visible author bios...
Read guide →Fact Density Measurement
Fact density counts verifiable claims per 1,000 words -named statistics, specific numbers, dated references, attributable statements. In our...
Read guide →Definition Pattern Detection
Definition patterns are sentence structures like "[Term] is [definition]" or "[Term] refers to [explanation]" that AI systems extract...
Read guide →Content Publishing Velocity
Content velocity tracks new pages and substantial updates over a rolling 90-day window. Sites publishing at least weekly...
Read guide →Supplementary Guides
Advanced implementation guides for specialized schema and internationalization.
Product & Offer Schema
Product and Offer schema audit checks that commerce pages include Product type with name, description, price, availability, and...
Read guide →Speakable Schema Markup
Speakable schema identifies content sections optimized for audio delivery by voice assistants. Adding Speakable markup to key paragraphs...
Read guide →Hreflang & Multilanguage Support
Hreflang audit checks that multilingual pages have correct hreflang tags with valid language-region codes, reciprocal references between versions,...
Read guide →ai.txt & TDM Policy
ai.txt is an emerging standard (like robots.txt for licensing) declaring whether AI systems may use your content for...
Read guide →Brand Mention Monitoring
Brand mention monitoring scans high-authority pages across the web for references to your brand and your competitors. Pages...
Read guide →Intelligence Report
10 AI-evaluated signals - does your content actually get cited?
Content Depth Score: What AI Engines Actually Want to Read
Content depth score feeds your page to an AI model and asks: "Does this cover the topic thoroughly...
Read guide →Citation-Ready Content Patterns: Writing Sentences AI Can Actually Use
Citation-ready patterns are specific content structures AI engines preferentially extract: attributable claims with sources, self-contained factual statements, comparative...
Read guide →Topic Authority Clustering: Why One Good Page Isn't Enough
Topic authority clustering maps your content into topic groups and evaluates whether you cover enough related subtopics to...
Read guide →Content Uniqueness Analysis: Do You Have Anything AI Doesn't Already Know?
Content uniqueness analysis uses AI to identify what percentage of your content provides information not readily available elsewhere....
Read guide →Author & Person Schema Depth: From Name String to Verified Expert
Author schema depth goes beyond checking if Person schema exists. It evaluates whether the markup includes enough detail...
Read guide →Wikidata & Knowledge Graph Presence: The External Trust Loop
Wikidata and Knowledge Graph presence means your business has a verified entry in public knowledge databases AI engines...
Read guide →Social Profile Verification: When sameAs Links Backfire
Social profile verification goes beyond checking sameAs URLs exist. It confirms linked profiles are active, contain consistent business...
Read guide →AI Hallucination Audit: What AI Engines Are Making Up About You
The AI hallucination audit asks multiple AI engines direct questions about your business and checks responses for accuracy....
Read guide →Live Citation Test: Does AI Actually Mention You?
The live citation test submits real user-style queries to ChatGPT, Claude, and Perplexity, then analyzes whether your domain...
Read guide →Cross-Engine Consistency Score: The 10-Point Gap That Changes Everything
Cross-engine consistency measures the variance in your scores, citation rates, and visibility across different AI engines. A gap...
Read guide →Original Data Pipeline: How AI Collects Proprietary Evidence for Every Article
The Original Data Pipeline is a five-stage system that automatically collects live web intelligence from news, academic, government,...
Read guide →ChatGPT Optimization
7 criteria that drive ChatGPT's citation decisions. Bing-first, recency-biased.
ChatGPT Conversational Query Matching -Why Keywords Don't Cut It
ChatGPT doesn't match keywords. It matches conversations. Your content needs to sound like one human explaining something to...
Read guide →ChatGPT Direct Answer Paragraphs -The Unit of Citation
ChatGPT pulls self-contained paragraphs -2-4 sentences that answer a question without needing anything else on the page. The...
Read guide →ChatGPT & Bing Indexation -The Gate You Didn't Know Existed
ChatGPT uses Bing as its retrieval backend. Not indexed by Bing? Invisible to ChatGPT. Period. Tidio (63) actively...
Read guide →ChatGPT Content Retrievability -Indexed Doesn't Mean Found
Retrievability measures whether ChatGPT actually finds your pages when relevant queries come in. Indexed by Bing? Necessary. Sufficient?...
Read guide →ChatGPT Q&A Distribution -How Many Questions Are You Missing?
Q&A distribution maps your question-answer content against questions ChatGPT users actually ask. Every gap -a question people ask...
Read guide →ChatGPT Recency Bias -Stale Content Disappears
ChatGPT inherits Bing's recency bias -recently published or updated content gets retrieved more often. Content with dateModified within...
Read guide →ChatGPT Comparison Table Extraction -Your Secret Weapon for "vs" Queries
ChatGPT extracts and restructures HTML comparison tables into its answers for "vs" queries. But here's what it actually...
Read guide →Claude Optimization
7 criteria Claude weighs most. Governance-first, structured-data-heavy.
How Claude Scores Your llms.txt (It's Not Pass/Fail)
Claude grades llms.txt on four levels: Level 1 (exists with basic description), Level 2 (structured URLs for key...
Read guide →The ClaudeBot Directive: Two Lines That Change Your Score
Claude penalizes sites that don't explicitly mention ClaudeBot in robots.txt - even if GPTBot and PerplexityBot are welcomed....
Read guide →Claude's Compound Trust Multiplier for JSON-LD
Claude applies a compound trust multiplier to JSON-LD: 1 schema type is baseline, 2 types give a small...
Read guide →Entity Disambiguation: Why Claude Skips You for Competitors
Claude uses a disambiguation algorithm that cross-references Organization schema, sameAs links, address data, and domain signals to distinguish...
Read guide →Content Licensing: The Permission Signal Claude Checks Before Citing You
Claude evaluates content licensing signals before deciding how freely to cite you. A CreativeCommons license, TDM Reservation Protocol...
Read guide →Semantic HTML: The Signal Claude Reads That ChatGPT Ignores
Claude performs deeper semantic HTML analysis than any other engine. It evaluates heading hierarchy (H1-H2-H3 nesting without gaps),...
Read guide →Fact Blocks: The Content Pattern Claude Cites First
Claude preferentially cites content structured as fact blocks: a named claim, followed by evidence or source, followed by...
Read guide →AEO for Startups
AI visibility strategy for early-stage startups and accelerator alumni.
AEO for Startups: Why AI Visibility Matters Before Product-Market Fit
Startups that set up llms.txt, Organization schema, robots.txt AI directives, and a basic FAQ in their first week...
Read guide →The 5 Quick Wins That Move a Startup from 30 to 60
Five changes that consistently produce a 25-30 point score lift: (1) llms.txt at domain root, (2) Organization +...
Read guide →What 2,500 YC Startup Audits Reveal About AI Readiness
Across 2,500+ YC startups audited from 12 batches, the average AEO Site Rank is 38/100. Only 2% score...
Read guide →AEO vs SEO for Startups: What Early-Stage Founders Get Wrong
SEO requires domain authority built over months. AEO requires technical infrastructure built in hours. For an early-stage startup,...
Read guide →Your Series A Pitch Deck Needs an AEO Site Rank
Investors increasingly use AI assistants to research markets, evaluate competitors, and validate startup claims. A startup with strong...
Read guide →How Top YC Startups Get Discovered by AI Engines
The highest-scoring YC alumni share a playbook: comprehensive llms.txt, 4+ schema types with compound trust, extensive FAQ and...
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