Claims are backed by specifics
Why it matters
AI systems citation-rank on specificity — a claim like "20-40 checks per audit, 62/100 average score on first run" is quotable and gets surfaced, while "powerful, industry-leading, seamless" is discarded as marketing noise. Sites dominated by unsubstantiated superlatives lose citation share to competitors whose pages contain named mechanisms, numeric outcomes, and concrete comparisons, even when the underlying product is weaker.
Severity rationale
High because vague marketing claims are systematically filtered out of AI answers in favor of specific, evidence-backed ones.
Remediation
Audit marketing copy across the homepage, pricing page, and feature pages. For every claim, add at least one form of evidence: a specific number, a named mechanism, a measurable outcome, or a concrete comparison. Replace adjectives with facts in src/app/page.tsx and src/app/(marketing)/page.tsx.
<p>22 checks across 4 categories. Projects score an average of 62/100 on their first audit.</p>
DetectionPro
The detection method for this pattern is part of AuditBuffet Pro.
The full method (what to look for, pass and fail conditions, and how results get reported) ships inside the GEO Readiness Audit. The pattern definition, severity rationale, and remediation remain openly licensed under CC-BY-4.0.
Taxons
History
- 2026-04-18·v1.0.0·Initial import from geo-readiness·automated