Reviews, ratings, and proof in machine-readable form, so AI can verify you're worth recommending.
Can AI verify you're worth recommending — your reviews, ratings, and proof in a form it can actually read?
When two businesses answer equally well, AI recommends the one whose reputation it can see.
Trust Signals are the reputation cues an agent can extract directly from your site: AggregateRating schema backed by a real rating and review count, an Organization.sameAs array linking your social and industry-directory profiles, and case studies with named clients and outcome metrics expressed as numbers, not adjectives. Agents weight self-declared authority heavily — but only when it's machine-readable.
When two pages have equally extractable answers, the agent picks the one whose author declares stronger reputation in parseable form. A site with AggregateRating schema, several sameAs links, and a case-study page with quantified outcomes outranks an identical site with no machine-readable identity layer.
AggregateRating schema with ratingValue ≥ 4.0 and a real reviewCount
Organization.sameAs linking to 3+ social platforms and an industry directory
A case-study/portfolio page reachable from the homepage with outcome metrics (numbers + %)
The free FACTS Score grades this pillar plus the other 4 — and tells you which specific findings are dragging it down.
Free FACTS Score01
The machine-readable facts that tell AI who you are, what you do, and where you work.
02
Clear, lift-ready answers to the questions your buyers actually ask.
03
The machine-readable doorways that let AI tools find, read, and do business with your site.
05
Honest, recent signals that tell AI you're still here — and still right.