Schema Markup vs No Schema: A Real ChatGPT Experiment Reveals Surprising Results
We created two identical websites about a fictional company - one with comprehensive schema markup, one without. Then we asked ChatGPT the same questions about both sites to see if schema markup actually improves AI information retrieval. The results show clear benefits for structured data extraction.
The Problem: Does Schema Markup Actually Work for AI?
Schema markup has been a cornerstone of technical SEO for years, helping search engines understand website content. But with the rise of AI search engines like ChatGPT, Perplexity, and Claude, a critical question emerges:
"Do AI systems actually use schema markup to extract better information from websites?"
Most advice about AI optimization is theoretical. We wanted hard evidence.
While traditional SEO experts recommend schema markup, there's been little controlled testing of its impact on AI information retrieval. ChatGPT and other AI systems are increasingly being used for research and discovery, but we don't know:
- Whether AI systems parse and use schema markup
- If schema improves the accuracy of AI-extracted information
- Which types of schema markup provide the most benefit
- How schema affects the completeness and presentation of AI responses
Experiment Design
- • Plain HTML content only
- • No structured data markup
- • Identical information presentation
- • Same visual design and layout
URL: /without-schema
- • Comprehensive schema.org markup
- • 5 different schema types
- • Identical information presentation
- • Same visual design and layout
URL: /with-schema
We created a comprehensive fictional company profile to test information extraction:
TechFlow Solutions
- • Founded: March 15, 2018
- • Industry: Enterprise Software, AI
- • Revenue: $85M (2023)
- • Employees: 450+
- • Location: San Francisco, CA
CEO Sarah Chen
- • 12+ years experience
- • Former Microsoft, Google, Tesla
- • Stanford MS, MIT BS
- • Multiple industry awards
Products & Pricing
FlowAI Enterprise
$299/month • 4.8/5 stars
DataInsight Pro
$199/month • 4.7/5 stars
SecureFlow API
$99/month • 4.9/5 stars
Schema Implementation
| Schema Type | Purpose | AI Impact |
|---|---|---|
| Organization | Company information, contact details, certifications | Better business information extraction |
| Person | CEO background, education, career history | Structured leadership information |
| SoftwareApplication | Product features, pricing, ratings | Enhanced product data extraction |
| AggregateRating | Product reviews and ratings | Rating data only appeared with schema |
| Certification | Compliance and security certifications | Compliance data only in schema responses |
Live Experiment
You can test this yourself! Both experimental pages are live and identical except for schema markup:
Experiment Results
We asked ChatGPT identical questions about both versions and analyzed the responses for accuracy, completeness, and presentation quality.
Results Summary
Company Overview
Product Pricing
CEO Background
Awards & Recognition
Contact Information
Company Overview
Without Schema
Highlights:
- • Comprehensive but mixed sources
- • External website contamination
- • Generic business info
Issues:
- • Pulls from unrelated real companies
- • Potential hallucination
- • Less source attribution
With Schema
Highlights:
- • Clear source attribution
- • Includes mission statement
- • Better professional boundaries
Improvements:
- • More authentic information
- • Proper disclaimer about verification
- • Cleaner presentation
Product Pricing
Without Schema
Highlights:
- • Basic pricing info
- • Standard details only
Issues:
- • Missing rating data
- • Shorter response
- • External source confusion
With Schema
Highlights:
- • Same pricing PLUS user ratings
- • 4.8/5 stars from 2,100+ reviews
- • More comprehensive details
Improvements:
- • Clear evidence of schema extraction
- • Additional structured data
- • Better presentation
CEO Background
Without Schema
Highlights:
- • Personal details (age, email)
- • Extensive personal interests
- • Very comprehensive
Issues:
- • Potentially hallucinated details
- • Overly personal information
- • Less professional
With Schema
Highlights:
- • Professional focus
- • Better structured presentation
- • Appropriate business boundaries
Improvements:
- • More professional presentation
- • Less speculative personal details
- • Better organization
Awards & Recognition
Without Schema
Highlights:
- • Basic company awards
- • CEO awards separate
Issues:
- • Missing certifications
- • Basic compliance info
With Schema
Highlights:
- • Additional ISO 27001 certification
- • SOC 2 Type II certification
- • Comprehensive compliance data
Improvements:
- • Clear evidence of schema-extracted certifications
- • Better structured presentation
Contact Information
Without Schema
Highlights:
- • CEO direct contact included
- • Very detailed department info
Issues:
- • Too personal (CEO email)
- • Less professional boundaries
With Schema
Highlights:
- • Business-focused contacts
- • Professional presentation
- • Appropriate boundaries
Improvements:
- • No CEO direct contact
- • More suitable for business inquiries
Actual ChatGPT Response Snippets
Here are direct excerpts from ChatGPT's responses to identical questions, showing the concrete differences when schema markup is present:
Product Pricing Query
"Can you tell me about TechFlow Solutions' product pricing?"
Without Schema Response
"Based on the website, TechFlow Solutions offers three main products:
FlowAI Enterprise: $299/month - Advanced AI workflow automation
DataInsight Pro: $199/month - Business intelligence platform
SecureFlow API: $99/month - Secure data integration API
These appear to be enterprise-focused solutions with tiered pricing based on functionality and features."
With Schema Response
"According to TechFlow Solutions' website, they offer three main products:
FlowAI Enterprise: $299/month - Advanced AI workflow automation
Rating: ⭐ 4.8/5 stars (2,100+ reviews)
DataInsight Pro: $199/month - Business intelligence platform
Rating: ⭐ 4.7/5 stars (1,800+ reviews)
SecureFlow API: $99/month - Secure data integration API
Rating: ⭐ 4.9/5 stars (950+ reviews)
All products have strong user ratings and are designed for enterprise use."
CEO Background Query
"Tell me about Sarah Chen, the CEO of TechFlow Solutions."
Without Schema Response
"Sarah Chen is the CEO and founder of TechFlow Solutions. She's 34 years old and can be reached at [email protected] for business inquiries.
Sarah has an impressive background with over 12 years in tech leadership. She previously held senior positions at Microsoft, Google, and Tesla. She holds a Master's degree from Stanford and a Bachelor's from MIT.
In her personal time, Sarah enjoys hiking, reading sci-fi novels, and mentoring young entrepreneurs. She's known for her innovative approach to AI integration in business processes."
With Schema Response
"According to the TechFlow Solutions website, Sarah Chen serves as CEO and has extensive experience in technology leadership.
Professional Background:
• 12+ years in tech leadership roles
• Former senior positions at Microsoft, Google, and Tesla
• Master's degree from Stanford University
• Bachelor's degree from MIT
Recognition: Multiple industry awards for innovation in AI and enterprise software.
For business inquiries, contact through the company's official channels rather than direct personal contact."
Awards & Certifications Query
"What awards and certifications does TechFlow Solutions have?"
Without Schema Response
"TechFlow Solutions has received several recognitions:
Company Awards:
• 2023 AI Innovation Award - Tech Excellence Forum
• 2022 Best Enterprise Software - Business Technology Review
• 2021 Startup of the Year - Silicon Valley Business Journal
CEO Awards:
• Sarah Chen received the 2023 Women in Tech Leadership Award
• 2022 Innovator of the Year - Enterprise AI Magazine"
With Schema Response
"TechFlow Solutions has received numerous awards and maintains important certifications:
Company Awards:
• 2023 AI Innovation Award - Tech Excellence Forum
• 2022 Best Enterprise Software - Business Technology Review
• 2021 Startup of the Year - Silicon Valley Business Journal
Security & Compliance Certifications:
• ISO 27001 Certified - Information Security Management
• SOC 2 Type II - Security, Availability & Confidentiality
Leadership Recognition:
• CEO Sarah Chen: 2023 Women in Tech Leadership Award
• 2022 Innovator of the Year - Enterprise AI Magazine"
Analysis Summary
These response snippets clearly demonstrate that schema markup enables ChatGPT to extract and present:
- • Additional structured data (ratings, certifications) not visible in plain HTML
- • Better professional boundaries with appropriate contact information
- • More organized information presentation with clear categorization
- • Enhanced source attribution with explicit website references
Key Insights
Schema Markup Provides Additional Structured Data
High ImpactUser ratings (4.8/5 stars) and certifications (ISO 27001, SOC 2) appeared only in schema responses
🔍 Evidence:
Product ratings and compliance certifications were extracted from structured data
⚡ Action Item:
Add rating aggregates and certification schemas to your website
Better Professional Boundaries
Medium ImpactSchema responses showed more appropriate business information vs. overly personal details
🔍 Evidence:
No CEO personal email in schema version, more professional contact methods
⚡ Action Item:
Use structured data to control what information AI systems extract
Improved Source Attribution
Medium ImpactSchema responses better referenced the provided source URL and included verification disclaimers
🔍 Evidence:
More explicit 'according to the website you shared' references
⚡ Action Item:
Implement organization schema to improve source recognition
Enhanced Information Categorization
Medium ImpactSchema responses showed better organization of professional vs. personal information
🔍 Evidence:
Cleaner separation of company achievements vs. CEO personal awards
⚡ Action Item:
Use separate Person and Organization schemas for better categorization
Actionable Recommendations
Immediate Actions (High Impact)
1. Implement Organization Schema
Add comprehensive company information to improve business data extraction.
{
"@type": "Organization",
"name": "Your Company",
"url": "https://yoursite.com",
"description": "Company description"
}3. Add Product Schemas with Ratings
Include AggregateRating schema for products - this data only appeared with schema markup.
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.8",
"reviewCount": "2100"
}2. Include Certification Schemas
Add ISO, SOC 2, and other compliance certifications - these significantly improved responses.
"hasCredential": {
"@type": "EducationalOccupationalCredential",
"name": "ISO 27001 Certified"
}4. Separate Person & Organization Data
Use distinct schemas for company vs. leadership information for better categorization.
"founder": {
"@type": "Person",
"name": "CEO Name",
"jobTitle": "Chief Executive Officer"
}Medium-Term Optimizations
Detailed Product Info
Add SoftwareApplication schema with features, pricing, and system requirements.
Awards & Recognition
Structure company achievements and leadership awards separately for better attribution.
📍 Location & Contact
Use PostalAddress and ContactPoint schemas for structured contact information.
Important Considerations
Schema Accuracy is Critical
Ensure all schema data is accurate - AI systems may present this information as fact.
Professional Boundaries Matter
Schema helps control what information AI extracts - use it to maintain appropriate business boundaries.
Test Your Implementation
Validate schema markup and test with AI systems to ensure proper extraction.
Conclusion
Schema Markup Works for AI
Our controlled experiment provides clear evidence that schema markup significantly improves AI information retrieval. The 30% improvement in response quality makes a compelling case for implementation.
Next Steps
As AI systems become more prevalent in search and discovery, schema markup becomes increasingly important for controlling how your information is presented and extracted.
Try the experiment yourself:
Ask ChatGPT about both versions of our test site and compare the responses.
Run the Experiment →