coingecko.com — AI Search Visibility Report
Overall score: 78/100
AI search visibility analysis for coingecko.com. LLMao scored coingecko.com 78/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 85/100 — High clarity and good jargon handling for a technical niche. Sentence lengths are appropriate for data-heavy content.
- schema_markup: 65/100 — Basic Organization schema is present and valid, but misses opportunities for Dataset, Article, or FAQ schemas.
- authority_trust: 75/100 — Strong trust signals through contact info and social links, but lacks specific author credentials for the market insights provided.
- citation_sources: 80/100 — Excellent use of primary data sources (Etherscan) and internal research reports, though external outbound citations are limited on the homepage.
- content_freshness: 100/100 — Exceptional freshness with real-time data and reports dated 2026-05-14. Clear update signals via 'about 2 hours ago'.
- content_structure: 70/100 — Good use of semantic HTML and organization, but heading hierarchy is weak with only one H1 and many sections lacking proper H2/H3 tags.
- entity_definition: 70/100 — Brand entity is well-defined, but individual author entities and specific term definitions lack structured markup.
- technical_accessibility: 70/100 — Meta descriptions and social tags are present, but 'noindex' signals in metadata are a major concern for LLM discovery.
Top recommendations
- Expand Structured Data to Content Blocks (Schema Markup): Implement Dataset schema for the market data tables and FAQPage schema for the 'What is Firo?' and 'Read more' sections to help LLMs parse structured data more efficiently.
- Implement Author Entities for Insights (Authority & Trust): Add visible author bylines and Person schema to the 'Market Insight' and 'Summary' sections to establish E-E-A-T for financial analysis.
- Verify Crawler Access Permissions (Technical Accessibility): The robots.txt or meta tags currently show 'noindex, nofollow' in the provided metadata. Ensure LLM crawlers (GPTBot, ClaudeBot) are explicitly allowed to ensure inclusion in RAG pipelines.
- Optimize Heading Hierarchy (Content Structure): Improve heading hierarchy by ensuring H2 and H3 tags are used for section titles like 'Highlights', 'Trending', and 'Top Gainers' which currently appear as plain text or links.
- Strengthen Term Definitions with Schema (Entity Definition): Create a dedicated 'Glossary' or 'Terms' section with DefinedTerm schema to help LLMs understand site-specific or industry-specific terminology.