The E in EEAT: Why Experience Matters for AI Search

Experience is the “first E” in E-E-A-T, added by Google in December 2022 to emphasize the importance of first-hand knowledge. For AI search, Experience signals help differentiate content based on real usage from content that's merely researched or rewritten. AI systems use these signals to identify sources worth citing—because content from someone who actually used a product or practiced a skill provides unique value that generic content cannot.

This guide explains what Experience signals AI looks for, why they matter more in the age of AI-generated content, and how to demonstrate real experience in your writing.

Why Google Added Experience to E-A-T #

In December 2022, Google updated its Search Quality Rater Guidelines to add “Experience” as a new component. The previous E-A-T (Expertise, Authoritativeness, Trustworthiness) became E-E-A-T.

The addition recognized a gap: expertise alone doesn't guarantee useful content. A nutritionist with a PhD has expertise in diet science, but someone who actually lost 50 pounds on a specific diet has experience. Both perspectives are valuable—but for different questions.

Experience vs. Expertise #

Google's guidelines now ask raters to consider: “Does the content creator have the necessary first-hand or life experience for the topic?” For product reviews, travel guides, and personal advice, Experience often matters more than formal credentials.

The 5 Experience Signals AI Looks For #

AI search engines evaluate experience through specific signals in your content. Here are the five key indicators:

Figure 1: The five experience signals

1. First-Person Narrative (E01) #

First-person pronouns combined with action verbs signal personal involvement:

• “I tested” — claims personal testing responsibility
• “We analyzed” — indicates team involvement
• “In my experience” — shares personal perspective
• “I discovered” — reveals learning through doing

2. Sensory Details (E02) #

Sensory descriptions indicate physical interaction with a subject:

• Visual: “The bright OLED display”
• Tactile: “The smooth, cold metal housing”
• Auditory: “A satisfying click with each keystroke”
• Weight/heft: “Heavier than expected at 3.2 pounds”

These details are hard to fake without actual interaction. Generic content describes features; experienced content describes how they feel.

3. Visual Evidence (E03) #

Original images prove real engagement:

• Product photos: The product on your desk, in your hand
• Screenshots: Your actual usage, dashboard views
• Before/after: Results from your testing
• Process images: Steps as you actually performed them

Stock photos don't demonstrate experience. Original images—even imperfect phone photos—signal authenticity.

4. Exclusive Data Points (E04) #

Precise measurements from actual testing create unique value:

• Specific numbers: “12.5ms response time” not “fast response”
• Test conditions: “At 75% brightness with WiFi on”
• Comparative data: “23% faster than the previous model”
• Time-based observations: “After 3 months of daily use”

Exclusive data points are AI citation magnets—they provide information that can't be found elsewhere.

5. Honest Critique (E05) #

Balanced perspectives including limitations signal authenticity:

• Cons section: What didn't work or could be better
• Limitations: Where the product falls short
• Who it's NOT for: Honest scoping
• Trade-offs: What you sacrifice for the benefits

Why AI Search Prioritizes Experience #

In the age of AI-generated content, Experience signals become even more important. Here's why:

The AI Content Problem #

AI can generate well-written, SEO-optimized content about products it has never used. This creates a flood of content that sounds authoritative but lacks genuine insight. Experience signals help differentiate:

• Human content based on real usage
• AI-generated content based on aggregated information
• Human-edited AI content with some experience layered in

Citation Value #

When AI search engines like Perplexity or Google SGE select sources to cite, they prefer content with unique information. Experience-based content provides:

• Original data: Measurements AI can't generate
• Real perspectives: Opinions backed by actual use
• Unique insights: Observations only experience reveals
• Credible critique: Honest assessment competitors may lack

Content with strong experience signals gets cited more often because it adds value that generic content cannot.

Experience Signals by Content Type #

Not all content requires the same level of experience demonstration. Here's how priorities shift:

High Experience Priority #

These content types need strong experience signals:

• Product reviews: All 5 signals critical
• Travel content: Photos, specific details, honest assessments
• Recipe/food content: Personal testing, photos of results
• Personal finance: Real results, actual experiences
• Health/fitness: Personal journey, measurable outcomes

Moderate Experience Priority #

These content types balance experience with expertise:

• How-to guides: Some first-person, emphasis on accuracy
• Comparison articles: Testing data valuable but not essential
• Industry analysis: Experience with the industry, not specific products

Lower Experience Priority #

These content types prioritize expertise over experience:

• Technical documentation: Accuracy over personal use
• News reporting: Expertise in reporting, not the topic
• Academic content: Credentials and citations matter more
• Legal/medical information: Professional expertise essential

How to Demonstrate Experience in Your Content #

Here's a practical guide to adding experience signals:

Step 1: Add First-Person Narrative #

Instead of:

"The iPhone 15 Pro has an excellent camera system."

Write:

"I've been using the iPhone 15 Pro's camera for 3 months. Here's what I've found..."

Step 2: Include Sensory Details #

Instead of:

"The build quality is good."

Write:

"The titanium frame feels noticeably lighter and cooler to the touch than the steel on my old phone."

Step 3: Add Original Images #

• Take your own photos (phone quality is fine)
• Include screenshots of your actual usage
• Show before/after results when relevant
• Add descriptive alt text referencing your experience

Step 4: Include Specific Data #

Instead of:

"Battery life is great."

Write:

"I got 8 hours 47 minutes of screen-on time with medium brightness and 5G enabled."

Step 5: Add Honest Critique #

Always include a “What I Didn't Like” or “Cons” section:

## What I Didn't Like

- The Action Button took weeks to become muscle memory
- USB-C cable compatibility varies more than expected  
- Price increase from the previous generation is hard to justify for minor upgrades

Frequently Asked Questions #

What if I haven't personally used the product? #

Be transparent. You can write valuable comparison content based on research, but clearly state your methodology. “Based on analyzing 50 user reviews” is honest and still useful—just different from first-hand testing.

Can AI detect fake experience signals? #

Increasingly, yes. AI can detect patterns that suggest fabricated experience—generic sensory descriptions, stock photo metadata, and inconsistencies in claimed testing. More importantly, readers can tell. Fake experience erodes trust quickly.

Does old experience still count? #

For evergreen topics, yes. For technology and fast-changing topics, recent experience matters more. Include dates when you tested or used something so readers (and AI) can assess relevance.

About the Author

Yue Zhu@Seenos.ai

Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.