Can Structured Data Boost AI and Search Traffic?

This video examines the results of a recent experiment conducted on a client’s website. The primary objective was to determine whether structured data could enhance traditional search metrics like clicks, visibility in SERP features, and AI-driven search traffic. Understanding how structured data influences these platforms is crucial as AI continues to reshape search and search engine optimization (SEO) strategies.

We found opportunities and questions for additional tests. We are learning what business owners can do to improve Google search visibility and expand features like AI chat search engines.

The Experiment: Linking Open Data for Better Search Visibility

This experiment aimed to increase the semantic enrichment of web pages by integrating linked open data—specifically, Wikidata references—to create stronger connections between page content and Google’s existing knowledge graph.

Google’s knowledge graph is built on structured relationships between entities, and Wikidata serves as a key linked data source that helps define those relationships. By associating our content with Wikidata entities, we aimed to improve Google’s understanding of the topics we covered and how they relate to existing knowledge structures.

To achieve this, we leveraged structured data, specifically article markup, and enriched it with:

• Mentions of key topics related to our content.
• Direct links to corresponding Wikidata articles, reinforcing semantic relationships.

This approach strengthens a page’s contextual relevance to Google, making it easier for search engines to process, rank, and display content within AI-powered search experiences, SERP features, and rich results.

The Hypothesis

The experiment was built on the following hypotheses:

The null hypothesis assumed nothing would change, while my main hypothesis predicted that adding these links to the article markup would enhance Google’s understanding of the page.

If correct, this would result in:

• Increased clicks
• Improved rich feature performance
• Higher AI Overview traffic
• More ChatGPT-driven traffic.

The Methodology

Mentions were integrated into the article schema markup, linking to Wikidata entries to establish a semantic connection between the website and the Linked Open Web.

How AI and Multi-Platform Strategies Are Changing SEO 

Let’s take a look at the results. 

Key Findings: How Structured Data Impacted Search Performance

After implementing the changes, we closely monitored the results using statistical tests to measure significance. The findings were compelling:

1. Click-Through Rate (CTR) and Organic Clicks Increased

One of the primary objectives was to assess whether structured data could lead to more organic clicks. To evaluate this, we conducted a paired t-test, a statistical method used to determine if there was a significant difference before and after the structured data implementation.

The test revealed that:

• Clicks increased after implementing the structured data changes.
• The p-value was < 0.05, meaning the increase in clicks was statistically significant and unlikely to be due to random chance.
• Since no other modifications were made to the site during this period, we can confidently attribute this increase to the structured data changes.

This suggests enhanced semantic signals help search engines understand page content more effectively, improving rankings and user engagement.

2. Boost in SERP Features: AI Overviews and Featured Snippets

Beyond traditional clicks, we examined how the test pages performed in SERP features, particularly Google AI Overviews and Featured Snippets. The structured data implementation led to a measurable increase in AI Overview appearances:

• The number of AI Overview rankings increased from 18 to 30.
• We ran a chi-square test, which confirmed that the increase was statistically significant (p-value < 0.05).
• The improved performance in rich features aligns with Google’s ongoing push for structured, machine-readable content.

This indicates that structured data may affect how Google selects and displays content in AI-driven SERP features.

3. AI Search Traffic: Not Just Google, But Other AI Platforms

The next aspect of our test focused on AI-driven traffic sources, including:

• Perplexity (an AI search engine that’s gaining traction)
• ChatGPT’s browsing feature
• Microsoft Copilot and other AI-driven search engines

Again, our statistical tests showed a significant increase in AI search-driven traffic. As AI continues to evolve as a discovery tool, this finding suggests that structured data may help improve visibility beyond just Google.

4. ChatGPT Traffic: No Significant Impact Yet

Interestingly, while we saw an increase in ChatGPT-related traffic, the statistical tests did not confirm that structured data directly impacted this source. 

Possible reasons include:

• ChatGPT’s crawling behavior is still unclear, and it may not be rendering JSON-LD data as efficiently as Google.
• JavaScript-rendered structured data may not be processed effectively by all AI-driven search platforms.
• Different indexing behaviors: Unlike Google, which continuously crawls and updates content, ChatGPT and similar AI models rely on periodic data refreshes.

This leads us to our next testing phase: hardcoding structured data directly into the HTML to determine whether ChatGPT’s ability to extract linked open data improves.

AI Search Optimization and SEO: What This Means

The results from this experiment highlight several key insights about how structured data and semantic enrichment impact SEO and AI-driven search:

• Semantic enrichment with structured data and Wikidata links enhances search engines’ ability to understand content, improving contextual relationships between entities.
• Increased visibility: Despite the rise of “zero-click searches,” structured data contributed to higher clicks and better performance in SERP features, helping mitigate the impact of zero-click trends. As AI Overviews, Perplexity, and other AI search tools evolve, structured data may play a role in securing content placement in these results.
• Future optimization: More testing is needed to understand how structured data impacts ChatGPT and other AI-driven discovery models. The next step is to experiment with hardcoded structured data rather than JavaScript-generated JSON-LD to see if it improves ChatGPT’s ability to extract and reference structured data.

Actionable Insights: How to Optimize for AI Search

If you’re looking to apply these findings to your SEO strategy, consider the following:

• Implement Semantic Markup: Adding structured data and Wikidata links helps search engines better comprehend your content, leading to improved rankings and rich feature placements.
• Monitor Performance: Track key metrics such as CTR, Rich Features, and AI Overview (AIO) traffic to measure the effectiveness of structured data implementations and make data-driven adjustments.
• Optimize for ChatGPT: AI-driven search is evolving, and optimizing for ChatGPT traffic means improving JSON integration on your site to ensure well-structured and AI-readable content.

By strategically leveraging structured data, we can stay ahead in an AI-dominated search landscape and improve visibility and user engagement.

Structured data is no longer just about traditional SEO—it’s crucial to optimizing for AI-driven search experiences. The key to success lies in continuously testing, refining, and adapting strategies to stay ahead in this ever-changing digital landscape. Until next time, happy marketing.