How it works
The analyzer scans your content for 8 classes of trust signal: author bylines, publication dates, external URLs, data sources ("according to X"), credentials (PhD, MD, etc), first-party evidence ("in our study"), named institutions and specific statistics. Each class is weighted by its impact on AI citation rate.
Why trust signals lift citations
- Assistants penalise unsourced claims - a confident claim without a source is treated as lower-grade than a hedged claim with one.
- Named authors carry accountability - anonymous content is discounted. A byline with credentials is worth 2-3x more.
- First-party data is irreplaceable - assistants can't get your internal numbers anywhere else, so they preferentially cite you for them.
- Institutional citations transfer trust - citing Stanford, Gartner or OECD lifts your own perceived authority.
Pair with
Combine with the Citation Probability Calculator for a weighted score, and the Fact Density Analyzer to quantify the numbers. Add Article schema with author + date fields to surface signals to structured extractors too. Full pattern: how assistants choose citations.