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coub.com
SUMMER 2016

coub.com

Weak AI visibility with 18 of 48 criteria passing. Biggest gap: llms.txt file.

42/100
F
Citation Avg
Answer Readiness
~40% weight
5/10
Content Structure
~25% weight
5/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
4/10
AI Discovery
~10% weight
4/10

Verdict

Critical AEO gaps at 42/100 - coub.com is largely invisible to AI engines. Key strengths include Content Cannibalization, Duplicate Content Blocks, and Cross-Page Duplicate Content. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed.

#9467of 13363
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How to Improve

Current
42/100
Projected
77/100
42Total Fixes
16Quick Wins
~99hEst. Effort
Quick Wins
Create /llms.txt fileStrengthen entity authority (NAP)Configure robots.txt for AI crawlersBuild FAQ sections with schemaLink orphan pages into site navigationImplement semantic HTML5 elementsAdd structured tables and listsAdd definition-style contentAdd direct answer paragraphsAdd ai.txt and content licensingIncrease fact and data densityFix canonical URL strategyImprove query-answer alignmentAdd visible date signalsMake pages solve the user task fasterImprove citation-ready writing quality
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Create complete sitemap.xml
critical|medium
Fix HTML structure and meta tags
medium|low
Configure robots.txt for AI crawlers
high|trivial
Fix canonical URL strategy
critical|low
Add internationalization signals
critical|medium
Improve server response efficiency
medium|low
Reduce render-blocking resources
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.

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.

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.

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

Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.

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.

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.

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