In this video, we dive deep into an SEO experiment testing the impact of structured data on search performance and AI-driven traffic. Discover how integrating linked open data with Wikidata and structured article markup can improve traditional search metrics—like click-through rates and rich feature performance—as well as boost AI traffic from platforms like Google and ChatGPT.
We cover:
• The hypothesis behind adding semantic enrichment to pages
• Step-by-step implementation of structured data using linked open data
• Statistical analysis (paired T-tests and chi-square tests) to measure impact
• Detailed results on clicks, rich features (IO and featured snippets), and AI search traffic
• Insights into why ChatGPT traffic did not show statistically significant improvement and next steps for testing
If you’re looking to optimize your website’s visibility and leverage structured data for enhanced AI search performance, this video is for you! Don’t forget to subscribe for more data-driven SEO insights and actionable tips.
Timestamps:
0:00 – Introduction & Experiment Overview
0:21 – Purpose: Testing Structured Data’s Impact on Search Metrics
0:45 – Semantic Enrichment: Leveraging Wikidata & Linked Open Data
1:24 – Hypothesis & Methodology: Enhancing Page Understanding
2:01 – Implementing Structured Data in Article Markup
2:28 – Analyzing Click-Through Rates: Paired T-Test Explained
3:08 – Statistical Significance & p-Values in SEO Testing
3:26 – Rich Feature Performance: Increase in IO & Featured Snippets
4:08 – Using Chi-Square Tests to Validate Rich Feature Gains
4:55 – Impact on AI Traffic: Google vs. ChatGPT
5:41 – Exploring ChatGPT’s Response to Structured Data
6:05 – Future Testing: Hard-Coding JSON for Improved Chat Search
7:14 – Key Takeaways & Actionable SEO Insights
7:38 – Monitoring Performance Beyond Average Ranks
7:56 – Final Thoughts: Experiment Results & Next Steps
8:14 – Conclusion & Call to Action: Subscribe for More Insights