Schema Markup vs No Schema: A Real ChatGPT Experiment Reveals Surprising Results

โ€ข12 min readโ€ขAI SEO

๐Ÿงช Experiment Summary

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.

๐Ÿค” 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:

  • โ“Whether AI systems parse and use schema markup
  • โ“If schema improves the accuracy of AI-extracted information
  • โ“Which types of schema markup provide the most benefit
  • โ“How schema affects the completeness and presentation of AI responses

๐Ÿ”ฌ Experiment Design

Controlled Variables

โŒ Without Schema

  • โ€ข Plain HTML content only
  • โ€ข No structured data markup
  • โ€ข Identical information presentation
  • โ€ข Same visual design and layout

URL: /without-schema

โœ… With Schema

  • โ€ข Comprehensive schema.org markup
  • โ€ข 5 different schema types
  • โ€ข Identical information presentation
  • โ€ข Same visual design and layout

URL: /with-schema

๐Ÿ“‹ Test Company Profile

We created a comprehensive fictional company profile to test information extraction:

๐Ÿข TechFlow Solutions

  • โ€ข Founded: March 15, 2018
  • โ€ข Industry: Enterprise Software, AI
  • โ€ข Revenue: $85M (2023)
  • โ€ข Employees: 450+
  • โ€ข Location: San Francisco, CA

๐Ÿ‘ฉโ€๐Ÿ’ผ CEO Sarah Chen

  • โ€ข 12+ years experience
  • โ€ข Former Microsoft, Google, Tesla
  • โ€ข Stanford MS, MIT BS
  • โ€ข Multiple industry awards

๐Ÿ’ป Products & Pricing

FlowAI Enterprise

$299/month โ€ข 4.8/5 stars

DataInsight Pro

$199/month โ€ข 4.7/5 stars

SecureFlow API

$99/month โ€ข 4.9/5 stars

๐Ÿ—๏ธ Schema Implementation

Schema TypePurposeAI Impact
OrganizationCompany information, contact details, certificationsBetter business information extraction
PersonCEO background, education, career historyStructured leadership information
SoftwareApplicationProduct features, pricing, ratingsEnhanced product data extraction
AggregateRatingProduct reviews and ratingsRating data only appeared with schema
CertificationCompliance and security certificationsCompliance data only in schema responses

๐ŸŒ Live Experiment

You can test this yourself! Both experimental pages are live and identical except for schema markup:

๐Ÿ“Š Experiment Results

We asked ChatGPT identical questions about both versions and analyzed the responses for accuracy, completeness, and presentation quality.

Results Summary

Company Overview

7/10
Without Schema
VS
9/10
With Schema

Product Pricing

6/10
Without Schema
VS
9/10
With Schema

CEO Background

7/10
Without Schema
VS
8/10
With Schema

Awards & Recognition

6/10
Without Schema
VS
9/10
With Schema

Contact Information

7/10
Without Schema
VS
8/10
With Schema
Schema Markup Average: 8.6/10
No Schema Average: 6.6/10
๐Ÿ“ˆ 30% Improvement with Schema Markup

Company Overview

7/10

Without Schema

โœ… Highlights:
  • โ€ข Comprehensive but mixed sources
  • โ€ข External website contamination
  • โ€ข Generic business info
โŒ Issues:
  • โ€ข Pulls from unrelated real companies
  • โ€ข Potential hallucination
  • โ€ข Less source attribution
9/10

With Schema

โœ… Highlights:
  • โ€ข Clear source attribution
  • โ€ข Includes mission statement
  • โ€ข Better professional boundaries
๐Ÿ“ˆ Improvements:
  • โ€ข More authentic information
  • โ€ข Proper disclaimer about verification
  • โ€ข Cleaner presentation

Product Pricing

6/10

Without Schema

โœ… Highlights:
  • โ€ข Basic pricing info
  • โ€ข Standard details only
โŒ Issues:
  • โ€ข Missing rating data
  • โ€ข Shorter response
  • โ€ข External source confusion
9/10

With Schema

โœ… Highlights:
  • โ€ข Same pricing PLUS user ratings
  • โ€ข 4.8/5 stars from 2,100+ reviews
  • โ€ข More comprehensive details
๐Ÿ“ˆ Improvements:
  • โ€ข Clear evidence of schema extraction
  • โ€ข Additional structured data
  • โ€ข Better presentation

CEO Background

7/10

Without Schema

โœ… Highlights:
  • โ€ข Personal details (age, email)
  • โ€ข Extensive personal interests
  • โ€ข Very comprehensive
โŒ Issues:
  • โ€ข Potentially hallucinated details
  • โ€ข Overly personal information
  • โ€ข Less professional
8/10

With Schema

โœ… Highlights:
  • โ€ข Professional focus
  • โ€ข Better structured presentation
  • โ€ข Appropriate business boundaries
๐Ÿ“ˆ Improvements:
  • โ€ข More professional presentation
  • โ€ข Less speculative personal details
  • โ€ข Better organization

Awards & Recognition

6/10

Without Schema

โœ… Highlights:
  • โ€ข Basic company awards
  • โ€ข CEO awards separate
โŒ Issues:
  • โ€ข Missing certifications
  • โ€ข Basic compliance info
9/10

With Schema

โœ… Highlights:
  • โ€ข Additional ISO 27001 certification
  • โ€ข SOC 2 Type II certification
  • โ€ข Comprehensive compliance data
๐Ÿ“ˆ Improvements:
  • โ€ข Clear evidence of schema-extracted certifications
  • โ€ข Better structured presentation

Contact Information

7/10

Without Schema

โœ… Highlights:
  • โ€ข CEO direct contact included
  • โ€ข Very detailed department info
โŒ Issues:
  • โ€ข Too personal (CEO email)
  • โ€ข Less professional boundaries
8/10

With Schema

โœ… Highlights:
  • โ€ข Business-focused contacts
  • โ€ข Professional presentation
  • โ€ข Appropriate boundaries
๐Ÿ“ˆ Improvements:
  • โ€ข No CEO direct contact
  • โ€ข More suitable for business inquiries

๐Ÿ“ Actual ChatGPT Response Snippets

Here are direct excerpts from ChatGPT's responses to identical questions, showing the concrete differences when schema markup is present:

๐Ÿ’ฐ Product Pricing Query

"Can you tell me about TechFlow Solutions' product pricing?"

โŒ 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."
Missing: User ratings, review counts, detailed feature comparisons

โœ… With Schema Response

"According to TechFlow Solutions' website, they offer three main products:

FlowAI Enterprise: $299/month - Advanced AI workflow automation
Rating: โญ 4.8/5 stars (2,100+ reviews)

DataInsight Pro: $199/month - Business intelligence platform
Rating: โญ 4.7/5 stars (1,800+ reviews)

SecureFlow API: $99/month - Secure data integration API
Rating: โญ 4.9/5 stars (950+ reviews)

All products have strong user ratings and are designed for enterprise use."
Added: User ratings, review counts extracted from schema markup

๐Ÿ‘ฉโ€๐Ÿ’ผ CEO Background Query

"Tell me about Sarah Chen, the CEO of TechFlow Solutions."

โŒ 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."
Issues: Personal email exposed, overly personal details, potentially speculative information

โœ… With Schema Response

"According to the TechFlow Solutions website, Sarah Chen serves as CEO and has extensive experience in technology leadership.

Professional Background:
โ€ข 12+ years in tech leadership roles
โ€ข Former senior positions at Microsoft, Google, and Tesla
โ€ข Master's degree from Stanford University
โ€ข 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."
Improvements: Professional boundaries maintained, structured presentation, appropriate contact guidance

๐Ÿ† Awards & Certifications Query

"What awards and certifications does TechFlow Solutions have?"

โŒ Without Schema Response

"TechFlow Solutions has received several recognitions:

Company Awards:
โ€ข 2023 AI Innovation Award - Tech Excellence Forum
โ€ข 2022 Best Enterprise Software - Business Technology Review
โ€ข 2021 Startup of the Year - Silicon Valley Business Journal

CEO Awards:
โ€ข Sarah Chen received the 2023 Women in Tech Leadership Award
โ€ข 2022 Innovator of the Year - Enterprise AI Magazine"
Missing: Security certifications, compliance standards

โœ… With Schema Response

"TechFlow Solutions has received numerous awards and maintains important certifications:

Company Awards:
โ€ข 2023 AI Innovation Award - Tech Excellence Forum
โ€ข 2022 Best Enterprise Software - Business Technology Review
โ€ข 2021 Startup of the Year - Silicon Valley Business Journal

Security & Compliance Certifications:
โ€ข ISO 27001 Certified - Information Security Management
โ€ข SOC 2 Type II - Security, Availability & Confidentiality

Leadership Recognition:
โ€ข CEO Sarah Chen: 2023 Women in Tech Leadership Award
โ€ข 2022 Innovator of the Year - Enterprise AI Magazine"
Added: ISO 27001 and SOC 2 certifications only appeared with schema markup

๐Ÿ” Analysis Summary

These response snippets clearly demonstrate that schema markup enables ChatGPT to extract and present:

  • โ€ข Additional structured data (ratings, certifications) not visible in plain HTML
  • โ€ข Better professional boundaries with appropriate contact information
  • โ€ข More organized information presentation with clear categorization
  • โ€ข Enhanced source attribution with explicit website references

๐Ÿ’ก Key Insights

1

Schema Markup Provides Additional Structured Data

High Impact

User ratings (4.8/5 stars) and certifications (ISO 27001, SOC 2) appeared only in schema responses

๐Ÿ” Evidence:

Product ratings and compliance certifications were extracted from structured data

โšก Action Item:

Add rating aggregates and certification schemas to your website

2

Better Professional Boundaries

Medium Impact

Schema responses showed more appropriate business information vs. overly personal details

๐Ÿ” Evidence:

No CEO personal email in schema version, more professional contact methods

โšก Action Item:

Use structured data to control what information AI systems extract

3

Improved Source Attribution

Medium Impact

Schema responses better referenced the provided source URL and included verification disclaimers

๐Ÿ” Evidence:

More explicit 'according to the website you shared' references

โšก Action Item:

Implement organization schema to improve source recognition

4

Enhanced Information Categorization

Medium Impact

Schema responses showed better organization of professional vs. personal information

๐Ÿ” Evidence:

Cleaner separation of company achievements vs. CEO personal awards

โšก Action Item:

Use separate Person and Organization schemas for better categorization

๐Ÿš€ 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

๐Ÿ“Š Detailed Product Info

Add SoftwareApplication schema with features, pricing, and system requirements.

๐Ÿ† Awards & Recognition

Structure company achievements and leadership awards separately for better attribution.

๐Ÿ“ Location & Contact

Use PostalAddress and ContactPoint schemas for structured contact information.

โš ๏ธ Important Considerations

โš ๏ธ

Schema Accuracy is Critical

Ensure all schema data is accurate - AI systems may present this information as fact.

โš ๏ธ

Professional Boundaries Matter

Schema helps control what information AI extracts - use it to maintain appropriate business boundaries.

โš ๏ธ

Test Your Implementation

Validate schema markup and test with AI systems to ensure proper extraction.

๐ŸŽฏ 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.

โœ…Additional structured data extraction
โœ…Better professional information boundaries
โœ…Improved source attribution
โœ…Enhanced information categorization

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 โ†’

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