fintonic.com — AI Search Visibility Report
Overall score: 68/100
AI search visibility analysis for fintonic.com. LLMao scored fintonic.com 68/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 90/100 — Excellent clarity and professional yet accessible tone.
- schema_markup: 60/100 — Basic Organization schema is present, but missing product-specific and FAQ schemas.
- authority_trust: 70/100 — Strong institutional trust (Bank of Spain license) but weak individual author authority.
- citation_sources: 40/100 — Lacks external citations for financial claims and data points.
- content_freshness: 25/100 — No visible publication or modification dates on the homepage.
- content_structure: 80/100 — Good use of H1 and H2, but lacks a clear Table of Contents for long-form sections.
- entity_definition: 75/100 — Brand identity is clear, but proprietary terms like FinScore need more structured definitions.
- technical_accessibility: 80/100 — Good meta tags and crawler access, but high dependency on JS for interactive elements.
Top recommendations
- Expand Content-Specific Schema (Schema Markup): Implement FAQPage schema for the 'Preguntas frecuentes' section and Product/Offer schema for the loan simulations to help LLMs extract specific financial terms.
- Implement Author E-E-A-T Signals (Authority & Trust): Add explicit author bylines and Person schema to blog posts and financial guides to satisfy E-E-A-T requirements for YMYL (Your Money Your Life) content.
- Surface Modification Dates (Content Freshness): Add visible 'Last Updated' dates to financial product pages and the blog to signal content recency to LLM crawlers.
- Reduce JS Dependency for Core Content (Technical Accessibility): Ensure the loan simulator and country selector are fully functional without heavy JavaScript dependency, as LLMs may struggle with complex client-side state.
- Formalize Entity Definitions (Entity Definition): Create a dedicated 'Glossary' or 'Term Definitions' section to define proprietary terms like 'FinScore' more explicitly for LLM knowledge graphs.