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vela.eco

vela.eco

Moderate AI visibility with 26 of 48 criteria passing. Biggest gap: llms.txt file.

50/100
1 since v1
F
Citation Avg
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
5/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
4/10

Verdict

Below-average AEO readiness at 50/100 - multiple areas need attention. Key strengths include Entity Authority & NAP Consistency, Fact & Data Density, and Canonical URL Strategy. Priority gaps: llms.txt File, RSS/Atom Feed, and Speakable Schema.

#5469of 13363
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How to Improve

Current
50/100
Projected
80/100
41Total Fixes
15Quick Wins
~79hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersLink orphan pages into site navigationImplement semantic HTML5 elementsAdd definition-style contentAdd direct answer paragraphsAdd ai.txt and content licensingEnhance author and expert schemaAdd visible date signalsMake pages solve the user task fasterImprove citation-ready writing qualityClarify entity boundariesReduce extraction frictionFix duplicate content blocksEliminate cross-page duplicate content
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Fix HTML structure and meta tags
medium|low
Configure robots.txt for AI crawlers
high|trivial
Create complete sitemap.xml
medium|low
Add internationalization signals
critical|medium
Reduce document weight
medium|low
Improve server response efficiency
medium|low
Reduce render-blocking resources
medium|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.

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

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.

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 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.

Sections within pages contain identical or near-identical text. LLMs may flag this as low-quality or thin content, reducing citation authority. Rewrite duplicate blocks with unique angles.

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.

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.

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.

Fix It With AI43

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Site Pages

www.vela.eco/industries/apparelF35
Vela™ I Apparel
www.vela.eco/styles/vela-hybridD42
Vela™ Hybrid
www.vela.eco/styles/plusD43
Vela™ Plus
Changes since v1Last audited 52 days ago
49
50
+1
View full comparison →
Add Original Data & Case StudiesImprove Question-Answer AlignmentAdd Structured Tables & ListsRestructure Content as Q&AFocus Content on Core TopicsFix Duplicate Content BlocksAdd Direct Answer ParagraphsAdd Owned Data SignalsAdd Content Freshness SignalsIncrease Content Depth

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