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cyberpolicy.com

cyberpolicy.com

Moderate AI visibility with 25 of 48 criteria passing. Biggest gap: llms.txt file.

Finance & PaymentsInsurance Services
52/100
F
Citation Avg
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
7/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
3/10
AI Discovery
~10% weight
4/10

Verdict

Below-average AEO readiness at 52/100 - multiple areas need attention. Key strengths include Direct Answer Paragraphs, Answer-First Placement, and Evidence Packaging. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed.

#6968of 26585
#425of 1391 in Finance & Payments
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How to Improve

Current
52/100
Projected
80/100
43Total Fixes
12Quick Wins
~96hEst. Effort
Quick Wins
Create /llms.txt fileAdd question-based headingsFix HTML structure and meta tagsConfigure robots.txt for AI crawlersAdd ai.txt and content licensingEnhance author and expert schemaFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsIncrease content depth and structureReduce extraction frictionReduce render-blocking resources
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Fix HTML structure and meta tags
high|low
Configure robots.txt for AI crawlers
high|trivial
Fix canonical URL strategy
critical|low
Add internationalization signals
critical|medium
Reduce render-blocking resources
high|low
Create complete sitemap.xml
medium|low
Improve server response efficiency
low|low
Reduce document weight
low|low

Top Opportunities10

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.

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.

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.

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.

Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.

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

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.

Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.

Fix It With AI43

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Site Pages

www.cyberpolicy.com/business-insurance/georgiaF36
CyberPolicy | Business insurance in Georgia
www.cyberpolicy.com/business-insurance/wyomingF36
CyberPolicy | Business insurance in Wyoming
www.cyberpolicy.com/business-insurance/marylandF36
CyberPolicy | Business insurance in Maryland
www.cyberpolicy.com/business-insurance-professions/person...F39
CyBerPolicy | Business Insurance for Personal Trainers
www.cyberpolicy.com/business-insurance-professions/restau...D40
CyBerPolicy | Business Insurance for Restaurants

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