E-E-A-T Analysis
Measure and optimize your content's Experience, Expertise, Authoritativeness, and Trustworthiness—the key factors AI systems use to evaluate source credibility.
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What is E-E-A-T?
E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It's a framework originally developed by Google to evaluate content quality, and it has become even more critical in the age of AI-powered search. AI systems like ChatGPT, Claude, and Perplexity rely on E-E-A-T signals to determine which sources to cite and trust.
Why E-E-A-T Matters for AI SEO
When AI systems generate responses, they must choose between millions of potential sources. E-E-A-T signals help them identify content that is reliable, accurate, and created by qualified individuals or organizations. Strong E-E-A-T signals significantly increase your chances of being cited.
The Four Pillars
Experience👤
First-hand experience with the topic. Shows you've actually used a product, visited a place, or done what you're writing about.
Expertise🎓
Deep knowledge and qualifications in the subject matter. Credentials, education, and demonstrated skill in the field.
Authoritativeness🏆
Recognition as a go-to source in your field. References from other authoritative sources, industry standing, and reputation.
Trustworthiness🛡️
Accuracy, transparency, and reliability. Honest content with proper citations, clear policies, and secure site operation.
E-E-A-T Score Ranges
AI unlikely to cite
Some signals present
Good credibility signals
Highly authoritative
YMYL Topics Require Higher E-E-A-T
"Your Money or Your Life" (YMYL) topics—health, finance, safety, legal matters—require exceptionally strong E-E-A-T signals. AI systems are especially cautious about citing sources for these topics.
Experience Signals
Experience is the newest addition to E-A-T (making it E-E-A-T), and it's increasingly important for AI citation. It demonstrates that you've actually done what you're writing about—not just researched it.
Why Experience Matters to AI
AI systems can now detect patterns that indicate genuine first-hand experience versus content that's simply aggregated from other sources. Authentic experience leads to unique insights, specific details, and practical knowledge that AI prioritizes when selecting citations.
Key Experience Signals
First-Person Narratives
Use "I did", "We tested", "In my experience" to show direct involvement
"After using this tool for 6 months, I found that..."
Specific Details
Include precise numbers, dates, and observations only someone with real experience would know
"The setup took exactly 47 minutes, and the main challenge was..."
Original Photos/Videos
Visual content showing actual use, behind-the-scenes, or real results
Screenshots of dashboards, before/after photos, walkthrough videos
Real Results & Data
Share actual outcomes from your experience with metrics and evidence
"Our conversion rate increased from 2.3% to 4.7% after implementing..."
Lessons Learned
Share mistakes, surprises, and non-obvious insights from your experience
"What nobody tells you is that the initial learning curve takes..."
How to Demonstrate Experience
✅ Do This
- • Share specific timelines of your experience
- • Include original images with metadata
- • Mention real challenges you faced
- • Provide concrete recommendations
- • Update content with ongoing experience
❌ Avoid This
- • Generic, vague descriptions
- • Stock photos only
- • Paraphrasing other reviews
- • Claims without evidence
- • Writing about things you haven't done
💡 Pro Tip: Document Everything
Start documenting your experiences as they happen. Take screenshots, save data, write notes. This "experience bank" becomes invaluable when creating content later. The specificity it enables is exactly what AI systems look for.
Expertise Optimization
Expertise signals demonstrate that you have the knowledge and qualifications to speak authoritatively on a topic. For AI systems, expertise helps differentiate genuine authorities from well-written amateur content.
Author Credentials
The most important expertise signal is clear author attribution with visible credentials.
Types of Expertise Signals
Formal Credentials
Professional Experience
Published Work
Industry Recognition
Social Proof
Content Expertise Signals
Beyond author credentials, your content itself should demonstrate expertise through depth and accuracy.
Depth Indicators
- ✓Comprehensive topic coverage
- ✓Technical accuracy and precision
- ✓Nuanced explanations
- ✓Advanced concepts included
- ✓Industry-specific terminology
Quality Indicators
- ✓Proper citations and references
- ✓Clear methodology explanations
- ✓Acknowledgment of limitations
- ✓Up-to-date information
- ✓Fact-checked claims
⚠️ Common Expertise Mistakes
- • Anonymous content — Always attribute to a real person or entity
- • Outdated credentials — Update bios regularly, remove expired certifications
- • Overclaiming — Only claim expertise you can actually demonstrate
- • Missing context — Explain why your background is relevant to the topic
Analyze Your E-E-A-T Score
See how your content measures up across all four E-E-A-T dimensions and get actionable recommendations.
Open E-E-A-T Analyzer