echelon.health — AI Search Visibility Report
Overall score: 78/100
AI search visibility analysis for echelon.health. LLMao scored echelon.health 78/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 80/100 — Content is clear and professional, though some medical jargon (e.g., 'Cullinan Assessment') is brand-specific and needs more context.
- schema_markup: 60/100 — Basic JSON-LD present (Organization, WebSite), but lacks deep MedicalEntity or FAQ schema.
- authority_trust: 80/100 — Strong social proof with celebrity endorsements (James Caan) and CQC ratings, but lacks individual medical practitioner bios with schema.
- citation_sources: 70/100 — The website has improved its inline citations by adding a direct link to the NHS for a medical claim. Outbound links to authoritative sources are consistently present. However, there is still a lack of direct inline citations to primary clinical studies for many medical claims, and the site relies heavily on internal pages and testimonials for claim verification rather than external, independent evidence.
- content_freshness: 95/100 — Excellent freshness with blog posts dated as recently as today (March 9, 2026).
- content_structure: 85/100 — Good use of H1/H2 hierarchy and semantic sections, though some testimonial areas are repetitive in the HTML.
- entity_definition: 75/100 — Brand entity is well-defined, but medical concepts could be more formally defined for AI consumption.
- technical_accessibility: 80/100 — Good meta descriptions and social meta, but heavy reliance on visual 'Body Map' for core info.
Top recommendations
- Enhance Medical Entity Schema (Schema Markup): Implement MedicalWebPage and MedicalCondition schema to define the specific diseases screened (Cancer, CHD) and the medical devices used (MRI, CT).
- Individual Author/Expert Schema (Authority & Trust): Add detailed Person schema for the 'World Class Radiologists' mentioned. LLMs prioritize content attributed to verifiable medical experts (E-E-A-T).
- Strengthen Factual Citations (Citation & Source Quality): Add more outbound links to peer-reviewed medical journals or official health bodies (NHS, WHO) when making claims about disease detection rates.
- Formalize Term Definitions (Entity Definition): Create a dedicated glossary or 'Medical Facts' sub-pages that explicitly define technical terms like 'Coronary Heart Disease' or 'Liquid Biopsy' using 'definedTerm' schema.
- AI-Readable Interactive Content (Technical Accessibility): Ensure the 'Body Map' interactive element has a text-based fallback or detailed ARIA labels so LLM crawlers can index the anatomical data.
- Add direct inline citations to primary clinical studies (citation_sources): For all medical claims, especially those regarding disease detection and prevention, provide direct inline citations to peer-reviewed clinical studies or reputable medical research institutions. This will significantly enhance the verifiability and credibility of the information presented.
- Strengthen claim verification with independent evidence (citation_sources): To support claims such as being the 'world’s leading provider of Preventative Health Assessments', consider incorporating external, independent verification from recognized health organizations, industry awards (beyond self-submitted ones), or third-party audits. This moves beyond testimonials and internal case studies to provide more robust evidence.