aci.aero — AI Search Visibility Report
Overall score: 78/100
AI search visibility analysis for aci.aero. LLMao scored aci.aero 78/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 75/100 — Professional and clear, though some industry jargon (ASQ, APEX, AMPAP) is used without immediate definition on the landing page.
- schema_markup: 70/100 — Valid JSON-LD present but basic. Needs more specific content schemas (Article, FAQ, Event) to match the site's rich offerings.
- authority_trust: 80/100 — Strong organizational trust with clear contact info and social proof, but lacks individual author expertise signals.
- citation_sources: 70/100 — High-quality primary data provider, but lacks formal inline citations or outbound links to external peer-reviewed research on the homepage.
- content_freshness: 95/100 — Excellent recency with multiple 2026 dates and clear modification timestamps in metadata.
- content_structure: 75/100 — Good use of semantic HTML and organization, though heading hierarchy is slightly flat with multiple H1s.
- entity_definition: 80/100 — Clear brand consistency and dedicated about sections, though Person schema for leadership is missing from the homepage.
- technical_accessibility: 85/100 — Good meta descriptions and social tags; WordPress-based structure is generally accessible.
Top recommendations
- Enhance Organization Schema Depth (Schema.org Markup): Expand JSON-LD to include specific 'Organization' properties like 'address', 'contactPoint', and 'sameAs' links to social profiles to strengthen the Knowledge Graph entity.
- Implement Individual Author Attribution (Authority & Trust Signals): Add explicit author bylines and Person schema to blog posts and intelligence reports. Currently, content is attributed to 'ACI World' generally, which limits E-E-A-T.
- Fix Heading Hierarchy Nesting (Content Structure): Ensure a strict H1-H2-H3 hierarchy. The homepage uses multiple H1 tags for carousel items, which can dilute the primary entity focus for LLMs.
- Formalize Inline Citations for Data Claims (Citation & Source Quality): Include a 'References' or 'Sources' section for data-heavy claims in the Intelligence Hub previews to provide LLMs with verifiable primary source paths.
- Optimize Robots.txt for AI Agents (Technical Accessibility): Explicitly allow LLM crawlers (GPTBot, ClaudeBot) in robots.txt to ensure full indexing of gated or deep-directory intelligence resources.