{ "version": "v1", "description": "47-signal AEO/GEO scoring rubric for measuring whether a page will get cited by AI answer engines.", "totalSignals": 47, "categories": [ { "key": "structure", "label": "Structure", "weight": 0.25, "description": "How parseable your page is to an AI engine. Schema, headings, lists, tables, alt-text, OG meta. The substrate that makes everything else legible.", "signalCount": 13 }, { "key": "authority", "label": "Authority", "weight": 0.2, "description": "Whether your page reads as authored by an expert, citing real sources. Bylines, citations, statistics, quotations, freshness, technical terms.", "signalCount": 8 }, { "key": "content", "label": "Content", "weight": 0.25, "description": "Whether the page actually answers the buyer query — directly, completely, in the right register. BLUF, query coverage, sub-question coverage, readability.", "signalCount": 11 }, { "key": "trust", "label": "Trust", "weight": 0.1, "description": "Crawl-time + share-time trust signals: HTTPS, canonical, viewport, AI-bot access via robots/llms.txt, Twitter card, meta description.", "signalCount": 7 }, { "key": "eeat", "label": "E-E-A-T", "weight": 0.2, "description": "Google's framework for Experience, Expertise, Authoritativeness, Trustworthiness. First-person evidence, case studies, author credentials, brand entity in Wikidata, press mentions, privacy policy, contact info.", "signalCount": 8 } ], "signals": [ { "key": "structural-depth", "category": "structure", "label": "Structural depth (GEO-SFE)", "what": "Heading hierarchy + nested structure depth — H1→H2→H3 nesting that mirrors a real outline.", "why": "arXiv:2603.29979 shows a +17.3% citation lift for pages with measurable structural depth vs flat documents.", "howToFix": "Group your content under named H2 subsections. Use H3 for sub-points. Don't skip levels.", "source": "GEO-SFE (arXiv:2603.29979) + Aggarwal et al. NeurIPS 2024", "impactTier": "high" }, { "key": "internal-linking", "category": "structure", "label": "Internal linking", "what": "Links from this page to other pages on your site — signal of a navigable graph.", "why": "AI crawlers expand context via internal links the same way they crawl. Isolated pages get under-indexed.", "howToFix": "Add 5–10 internal links per page to related concepts, glossary terms, or supporting pages.", "source": "Anthropic web-search retrieval docs", "impactTier": "medium" }, { "key": "page-weight", "category": "structure", "label": "Page weight", "what": "Total HTML size, lower is better. We flag pages over 500 KB.", "why": "AI render bots have shorter timeouts than humans. Heavy pages get truncated or skipped.", "howToFix": "Strip unused JS, defer below-the-fold images, kill render-blocking third-party scripts.", "source": "Google SGE crawler docs", "impactTier": "standard" }, { "key": "json-ld-presence", "category": "structure", "label": "JSON-LD presence", "what": "Whether the page ships at least one schema.org JSON-LD block.", "why": "Schema.org is the single highest-leverage signal for AI Overview eligibility — engines parse it before text.", "howToFix": "Add at minimum an Organization or Article block. Our /tools/schema-generator outputs valid JSON-LD.", "source": "Google SGE evaluation guide", "impactTier": "high" }, { "key": "json-ld-validity", "category": "structure", "label": "JSON-LD validity", "what": "Whether the JSON-LD parses, has @context = schema.org, and a valid @type.", "why": "Malformed JSON-LD is worse than absent — engines log a parse error and downrank trust.", "howToFix": "Run your JSON-LD through Google's Rich Results Test before shipping.", "source": "Google SGE evaluation guide", "impactTier": "medium" }, { "key": "json-ld-relevance", "category": "structure", "label": "JSON-LD type relevance", "what": "Whether the @type matches the page intent (Article on a blog, Product on a PDP, FAQPage on a FAQ).", "why": "Wrong-type schema gets ignored — Article markup on a homepage is parsed as noise.", "howToFix": "Pick the closest schema.org type for the page's actual content, not a generic catch-all.", "source": "schema.org documentation", "impactTier": "medium" }, { "key": "faq-schema", "category": "structure", "label": "FAQ schema", "what": "FAQPage JSON-LD with at least 2 Q&A pairs.", "why": "FAQPage is the highest single-type lift for AI Overview citations per Google's own SGE guidance.", "howToFix": "Add FAQPage schema with 3–5 question/answer pairs that mirror real buyer queries.", "source": "Google SGE evaluation guide", "impactTier": "medium" }, { "key": "h1-quality", "category": "structure", "label": "H1 quality", "what": "Exactly one H1, length 20–70 chars, contains a primary query token.", "why": "AI engines treat H1 as the page's claim — multiple H1s confuse the topical model.", "howToFix": "One H1 per page, descriptive, 30–60 chars, includes the page's primary topic.", "source": "Google SGE crawler docs", "impactTier": "medium" }, { "key": "h2-coverage", "category": "structure", "label": "H2 coverage", "what": "≥3 H2 subsections that segment the content for skim-readability.", "why": "AI engines extract H2s as section anchors — pages without them are harder to summarize.", "howToFix": "Break content into 3–6 H2 subsections, each addressing a sub-question.", "source": "Aggarwal et al. NeurIPS 2024", "impactTier": "medium" }, { "key": "lists", "category": "structure", "label": "Lists", "what": "≥1