The 8 Citation Signals That Get You Cited

Eight measurable, weighted signals drive whether an AI answer engine cites a page — a synthesized field model, ranked from FAQ schema down to author attribution, with each weight to be verified against a primary source at build.

The eight weighted citation signals

Eight signals, in descending weight, drive whether an AI answer engine cites a page: FAQ schema (20%), answer-first structure (19%), statistical density (16%), heading structure (16%), freshness (8%), crawler access (8%), schema coverage (7%) and author attribution (6%). Each one is a concrete, measurable change you can make to a single page.

Source discipline: these weights are a synthesized field model assembled from public GEO/AEO research, not a measured law of physics. Treat the percentages as a relative ranking, not exact constants — each weight carries a verify against primary at build note, and the published page binds every figure to a primary source before it ships. The ordering (FAQ and answer-first dominate; author and schema-beyond-FAQ are tie-breakers) is the durable signal; the exact decimals are not.

Rank	Signal	Weight (model)	How to implement	Maps to readiness
1	FAQ schema	20%	Add FAQPage JSON-LD to genuine Q&A blocks	/agent-readiness/content
2	Answer-first structure	19%	Open each section with the liftable answer	/agent-readiness/content
3	Statistical density	16%	Use named numbers, dates and figures	/agent-readiness/content
4	Heading structure	16%	Most-important-noun-first H2/H3 hierarchy	/agent-readiness/content
5	Freshness	8%	Show a dated, last-verified timestamp	/agent-readiness/quality
6	Crawler access	8%	Let AI crawlers read the page (robots + render)	/agent-readiness/access-control
7	Schema coverage	7%	Add Article/Person/Breadcrumb structured data	/agent-readiness/discoverability
8	Author attribution	6%	Name a credentialed author with Person schema	/agent-readiness/quality

What each signal does, and how to build it

FAQ schema (20%) is the highest-weighted citation signal because it hands an answer engine a pre-structured question-and-answer pair it can lift verbatim. Add FAQPage JSON-LD to real Q&A blocks — and note that this very page implements it, so the technique is self-demonstrating.

Answer-first structure (19%) gets a page cited because the engine can quote the opening sentence without rewriting it. Lead every section with a standalone, declarative answer, then explain.

Statistical density (16%) raises citation likelihood because named numbers, dates and figures are exactly what a generative answer needs to substantiate a claim. Replace vague qualifiers with quantified, dated facts.

Heading structure (16%) helps because a most-important-noun-first hierarchy lets the engine map your page to a query. Put the key entity at the front of every H2 and H3.

Freshness (8%) contributes because engines prefer recently verified content for fast-moving topics. Show a visible last-verified date and keep it honest.

Crawler access (8%) is a precondition: an engine cannot cite a page its crawler cannot read. Permit the search-index and answer-engine crawlers in robots.txt and serve content without a render wall.

Schema coverage (7%) adds structured data beyond FAQ — Article, Person, BreadcrumbList — so the engine can resolve authorship, recency and hierarchy in one parse.

Author attribution (6%) raises citability because a named, credentialed author is an E-E-A-T signal the engine can verify. Attach a Person entity with real credentials.

The signals are agent-readiness signals

Every citation signal above is also an agent-readiness signal, so the same investment pays off in both the human-search channel and the LLM channel at once. FAQ schema, answer-first structure and schema coverage are the content and discoverability readiness checks; crawler access is the access-control check; freshness and author attribution are the quality and E-E-A-T checks. The cheapest way to do GEO is to make your site agent-ready and let the audit confirm it.

← GEO · .md