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trella.app
SUMMER 2019

trella.app

Weak AI visibility with 20 of 48 criteria passing. Biggest gap: llms.txt file.

39/100
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
5/10
Content Structure
~25% weight
3/10
Trust & Authority
~15% weight
2/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
2/10

Verdict

Critical AEO gaps at 39/100 - trella.app is largely invisible to AI engines. Key strengths include Duplicate Content Blocks, Cross-Page Duplicate Content, and Fact & Data Density. Priority gaps: llms.txt File, Schema.org Structured Data, and Q&A Content Format. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

#10605of 13363
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How to Improve

Current
39/100
Projected
76/100
44Total Fixes
16Quick Wins
~106hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersLink orphan pages into site navigationAdd definition-style contentAdd direct answer paragraphsAdd ai.txt and content licensingFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsFocus blog content on core expertiseAdd first-hand experience signalsMake content creators clearly visibleExplain how content was tested or reviewedAdd answer-first content placementImprove server response efficiencyReduce 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 HTML structure and meta tags
medium|low
Fix canonical URL strategy
critical|low
Reduce document weight
high|low
Add internationalization signals
critical|medium
Improve server response efficiency
high|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.

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.

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.

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.

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

Add Organization schema with consistent name, address, phone (NAP). Include sameAs links to social profiles and authoritative directories to strengthen entity recognition.

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.

Fix It With AI46

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Site Pages

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