akamai.com — AI Search Visibility Report
Overall score: 79/100
AI search visibility analysis for akamai.com. LLMao scored akamai.com 79/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 85/100 — Professional and clear, though technical jargon is heavy (expected for the industry). Sentence length is well-managed.
- schema_markup: 65/100 — Basic Organization schema is present and valid, but missing rich content schemas for reports and news.
- authority_trust: 75/100 — Strong corporate trust signals (contact info, social proof), but lacks individual author credentials for research reports.
- citation_sources: 70/100 — Cites major analysts (Gartner, IDC, Forrester) but lacks inline citations for specific data claims in the text.
- content_freshness: 85/100 — Excellent recency with multiple 2026 reports and updates visible. No clear 'last modified' date in metadata.
- content_structure: 70/100 — Good use of semantic HTML, but heading hierarchy is inconsistent (skipping levels).
- entity_definition: 80/100 — Strong brand consistency and clear 'About' context, though lacks specific Person entities for authors.
- technical_accessibility: 90/100 — Excellent meta descriptions and social tags. Content is largely accessible, though navigation is JS-heavy.
Top recommendations
- Expand Content-Specific Schema Markup (Schema Markup): Implement Article or BlogPosting schema for the numerous reports and news items featured on the homepage. Currently, only Organization schema is present.
- Implement Author Identification for Research Content (Authority & Trust): Add visible author bylines and Person schema for the research reports (e.g., SOTI reports). LLMs prioritize content with clear, verifiable human expertise.
- Optimize Heading Hierarchy (Content Structure): Fix the heading hierarchy. The page jumps from H1 to H5 in the navigation menu, and uses multiple H2s for layout elements rather than a logical content flow.
- Explicitly Allow AI Crawlers (Technical Accessibility): Ensure the robots.txt explicitly allows AI crawlers like GPTBot and ClaudeBot to ensure full indexing of technical documentation.
- Formalize Technical Term Definitions (Entity Definition): Create a dedicated 'Definitions' or 'Glossary' section for technical terms like 'Inference Cloud' or 'Edge Computing' to anchor entity understanding.