newrelic.com — AI Search Visibility Report
Overall score: 78/100
AI search visibility analysis for newrelic.com. LLMao scored newrelic.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: 75/100 — Professional and clear, though high density of technical jargon (APM, MTTR, IAST) without immediate definitions.
- schema_markup: 70/100 — Basic Organization and WebSite JSON-LD present. Missing Product, FAQ, or SoftwareApplication schemas for core offerings.
- authority_trust: 75/100 — Strong social proof and contact info, but lacks explicit editorial standards and author-level expertise on the homepage.
- citation_sources: 80/100 — Good use of primary sources (Google Sheets for pricing data) and customer testimonials, though few external outbound links.
- content_freshness: 85/100 — Excellent recency with 2026 event dates and 2025/2026 copyright/image signals. No explicit 'last modified' text.
- content_structure: 80/100 — Clear H1 and H2 hierarchy. Uses semantic HTML but could benefit from more distinct <article> or <section> wrapping for specific features.
- entity_definition: 70/100 — Strong brand consistency and 'About' presence, but lacks individual author identification for technical content.
- technical_accessibility: 90/100 — Excellent meta descriptions and social meta. Content is highly accessible.
Top recommendations
- Expand Content-Specific Schema (Schema.org Markup): Implement Product and FAQPage schema on the homepage to define specific platform capabilities and answer common user questions for LLM extraction.
- Formalize Trust Documentation (Authority & Trust Signals): Add a dedicated 'Editorial Standards' or 'Trust Center' link in the footer to strengthen E-E-A-T signals for LLMs.
- Implement Author Entities (Entity Definition): Create dedicated author bios for technical blog posts and documentation to establish 'Person' entities and expertise.
- Expose Modification Dates (Content Freshness): Ensure 'Last Updated' dates are visible on all technical documentation and platform pages to signal recency to LLM crawlers.
- Optimize AI Crawler Access (Technical Accessibility): Explicitly allow AI-specific crawlers (GPTBot, ClaudeBot) in robots.txt to ensure priority indexing of new features.