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wvinsurance.gov

wvinsurance.gov

Weak AI visibility with 16 of 48 criteria passing. Biggest gap: llms.txt file.

Finance & PaymentsInsurance Services
43/100
1 since v1
F
Citation Avg
Coherence gate active - score capped at 55
Answer Readiness
~40% weight
5/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
4/10
Technical Foundation
~10% weight
3/10
AI Discovery
~10% weight
2/10

Verdict

Critical AEO gaps at 43/100 - wvinsurance.gov is largely invisible to AI engines. Key strengths include Duplicate Content Blocks, Entity Density, and Table & List Extractability. Priority gaps: llms.txt File, Schema.org Structured Data, and Sitemap Completeness. Topic coherence is 4/10, which caps the overall score at 55. Focusing content on core expertise areas is the single highest-impact improvement.

#9376of 13363
#978of 1391 in Finance & Payments
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How to Improve

Current
43/100
Projected
77/100
45Total Fixes
13Quick Wins
~103hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd direct answer paragraphsAdd ai.txt and content licensingFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsFocus blog content on core expertiseMake pages solve the user task fasterReduce extraction frictionReduce render-blocking resourcesReduce document weight
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Create complete sitemap.xml
critical|medium
Configure robots.txt for AI crawlers
critical|low
Fix canonical URL strategy
critical|low
Improve server response efficiency
critical|medium
Reduce render-blocking resources
high|low
Reduce document weight
high|low
Fix HTML structure and meta tags
low|low
Add internationalization signals
critical|medium

Top Opportunities10

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

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.

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

Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

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.

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.

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

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.

Write self-contained definition sentences and single-claim statements that AI engines can quote directly. Avoid pronouns like "this" or "that" at the start of answer paragraphs.

Fix It With AI46

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Site Pages

www.wvinsurance.gov/Divisions_LicensingF36
Licensing and Education Division
www.wvinsurance.gov/PrivacyStatementD41
Privacy Statement
www.wvinsurance.gov/Consumer_Services_auto_termsF35
Auto Terms
www.wvinsurance.gov/Workers-CompensationF24
Workers' Compensation
www.wvinsurance.gov/company-homeD40
Company-Home
www.wvinsurance.gov/SAWCF35
State Agency Workers’ Compensation Plan
www.wvinsurance.gov/Divisions_Special-Investigations-Divi...F36
Special Investigations Division
Changes since v1Last audited 52 days ago
44
43
-1
View full comparison →
Focus Content on Core TopicsIncrease Content DepthRestructure Content as Q&AAdd Answer Capsule PatternsAdd Direct Answer ParagraphsAdd Owned Data SignalsAdd Original Data & Case StudiesPackage Evidence for AIAdd Entity DisambiguationImprove Citation-Ready Writing

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