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paragonvision.com

paragonvision.com

Weak AI visibility with 23 of 48 criteria passing. Biggest gap: llms.txt file.

Healthcare & Patient AdvocacyHospital & Health Care
49/100
2 since v1
F
Citation Avg
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
6/10
Trust & Authority
~15% weight
2/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
6/10

Verdict

Below-average AEO readiness at 49/100 - multiple areas need attention. Key strengths include Fact & Data Density, Canonical URL Strategy, and Content Cannibalization. Priority gaps: llms.txt File, Schema.org Structured Data, and Content Licensing & AI Permissions.

How to Improve

Current
49/100
Projected
78/100
42Total Fixes
12Quick Wins
~102hEst. Effort
Quick Wins
Create /llms.txt fileFix HTML structure and meta tagsStrengthen entity authority (NAP)Configure robots.txt for AI crawlersAdd ai.txt and content licensingEnhance author and expert schemaImprove query-answer alignmentAdd visible date signalsImprove citation-ready writing qualityAdd answer-first content placementReduce extraction frictionReduce render-blocking resources
Fix HTML structure and meta tags
high|low
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Reduce render-blocking resources
high|low
Configure robots.txt for AI crawlers
high|trivial
Add internationalization signals
critical|medium
Improve server response efficiency
medium|low
Reduce document weight
low|low
Create complete sitemap.xml
low|low

Top Opportunities10

Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.

Strengthen internal linking with descriptive anchor text between related pages. Add breadcrumb navigation and ensure every key page is reachable within 3 clicks from the homepage.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.

Fix It With AI41

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Site Pages

paragonvision.com/ecp/practitioner-resourcesF36
Practitioner Resources | Paragon Vision Sciences
Changes since v1Last audited 75 days ago
47
49
+2
View full comparison →
Increase Content DepthAdd Original Data & Case StudiesAdd Structured Tables & ListsAdd Owned Data SignalsPackage Evidence for AIImprove Internal Linking ArchitectureRestructure Content as Q&AImprove Question-Answer AlignmentAdd Content Freshness SignalsAdd Entity Disambiguation

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