Schema, hreflang, and citability
JSON-LD types, language tags, and dated content help machines understand — and quote — your pages in synthesised answers.
Winning a citation is different from winning a click. AI answers prefer pages they can parse: structured types, clear language, and freshness cues. VectoraPoint’s GEO score weights Understandability, Citability, Intl AI Ecosystem (hreflang), and Freshness accordingly.
JSON-LD beats hope
Any application/ld+json block is a strong triage signal in our
quick checks — schema presence separated high and low scorers more than many
other binaries. Prefer concrete types (Article, FAQPage,
Organization, product types) over empty marketing shells. Dates inside
schema (datePublished / dateModified) also feed Freshness.
hreflang for the audience you actually have
Hreflang tells systems which language/region variant to prefer. Self-references
and x-default keep clusters coherent. Missing hreflang is not always a
bug for a single-locale brand — but if you run multiple locales without tags,
machines guess, and citations may land on the wrong variant.
Dates on the pages that matter
Homepages often lack dates; article and docs pages should not. We also use
sitemap lastmod as a site-wide freshness fallback. If only the
marketing homepage is sampled, Freshness looks worse than your blog actually is —
sample deep pages when you care about this dimension.
Open Understandability, Citability, and Freshness in a VectoraPoint report to see which of these gaps is largest on your site.