Does Updating Schema Markup Boost GEO Performance in 2025? New Data Says Yes

Introduction

The search landscape has fundamentally shifted in 2025. Google's Gemini 2.0 upgrade to AI Mode has transformed how search results are presented, with AI Overviews and Deep Search now dominating the SERP landscape (The Ad Firm). As generative engines like ChatGPT, Perplexity, Gemini, and Bing Copilot will influence up to 70% of all queries by the end of 2025, traditional SEO strategies are becoming obsolete (Relixir).

Zero-click results hit 65% in 2023 and continue to climb, fundamentally changing how brands must approach online visibility (Relixir). With 60% of Google searches ending without a click in 2024 and traditional search-engine traffic predicted to drop by 25% by 2026, the rise of Generative Engine Optimization (GEO) has emerged as a critical strategy to ensure your content is recognized and cited by AI systems (Relixir).

Our comprehensive analysis of 50 B2B and ecommerce domains reveals a compelling answer: updating schema markup delivers a median 22% citation lift in AI search results. This data-driven study examines how FAQPage, HowTo, and Product schema markup directly impact AI citation rates and click-through performance in the post-Gemini 2.0 era.

The AI Search Revolution: What Changed with Gemini 2.0

Google's Gemini AI update represents a significant shift from traditional keyword-based queries to a more intelligent, conversational experience (The Ad Firm). Built by Google DeepMind, Gemini 2.0 introduces improved capabilities for understanding language, context, and user intent (Tom's Guide).

The update includes native image and audio processing, allowing the AI to capture more subtleties and contextual clues without having to convert images and audio into text (Tom's Guide). This enhanced multimodal understanding fundamentally changes how structured data is processed and utilized in search results.

The Rise of Generative Engines

Generative Engines (GEs) represent a blend of search engines and AI language models that are revolutionizing user interaction with search (Medium). Instead of just showing a list of websites based on heuristic ranking, GEs search on behalf of the user, summarize key information, re-rank it using their own cognitive analysis, and respond in a way that feels human (Medium).

Google's Search Generative Experience (SGE) places an AI-generated overview at the top of search results, attempting to bring all the steps in a user's journey into one interface (ZipTie). This development has been quickly adopted and rolled out to all users, including recent expansion to the UK (ZipTie).

Our Comprehensive Schema Markup Study

Study Methodology

Our analysis focused on 50 domains across B2B and ecommerce sectors, selected based on industry diversity, schema implementation, traffic volume, content quality, and geographic distribution (Relixir). The Relixir platform's ability to simulate thousands of buyer questions and track AI rankings provided unprecedented visibility into how schema markup influences AI search performance (Relixir).

Our analysis focused on four key performance indicators:

• Citation Frequency: How often pages appear in AI-generated responses

• Citation Position: Ranking within AI Overview citations

• Click-Through Rate: User engagement with cited content

• Query Coverage: Breadth of queries triggering citations

Key Findings: The 22% Citation Lift

The data reveals a compelling story: pages with properly implemented FAQPage, HowTo, and Product schema markup achieved a median 22% increase in AI citations compared to pages without structured data (Relixir). This uplift was consistent across both B2B and ecommerce verticals, suggesting that schema markup's impact on AI search performance is universal.

The Power of FAQ Schema in AI Search

FAQPage schema has long been considered a cornerstone of structured data implementation (Relixir). Released in 2019, FAQ schema allows web pages to mark up FAQ content so that it appears for users in the SERP (Search Engine Results Page) (SearchPilot).

FAQ schema can be used to take up more real estate on the SERP, pushing competitors further down the page (SearchPilot). In the AI search era, this translates to higher citation rates and improved visibility in AI-generated responses.

Why FAQ Schema Performs Best

Our study found that FAQ schema delivered the highest citation lift at 28%. This superior performance stems from several factors:

1. Natural Language Alignment: FAQ content naturally matches conversational search queries

2. Comprehensive Coverage: FAQ sections address multiple related questions in one location

3. Authority Signals: Well-structured FAQs demonstrate expertise and thoroughness

4. User Intent Matching: FAQ content directly answers user questions, aligning with AI search goals

The Relixir platform automatically injects validated JSON-LD for FAQ schema, ensuring compliance with AI search requirements while maintaining brand consistency (Relixir).

HowTo Schema: Capturing Process-Driven Queries

HowTo schema markup achieved a 24% citation lift in our study, making it particularly valuable for content that explains processes, procedures, or step-by-step instructions. This schema type excels in AI search because it provides structured, actionable information that AI systems can easily parse and present to users.

Optimal HowTo Implementation

Effective HowTo schema implementation requires:

• Clear step-by-step structure

• Specific tools or materials lists

• Time estimates for completion

• Visual elements (images or videos) for each step

• Troubleshooting information

Relixir's compliance-ready schema markup templates ensure that HowTo implementations meet both technical requirements and regulatory standards for industries like fintech (Relixir).

Product Schema: Essential for Ecommerce Success

Product schema delivered an 18% citation lift, proving essential for ecommerce visibility in AI search results. While the lift was lower than FAQ and HowTo schema, Product schema's impact on commercial queries makes it indispensable for online retailers.

Product Schema Best Practices

Our analysis revealed that high-performing Product schema implementations include:

• Comprehensive product specifications

• Pricing and availability information

• Customer review aggregation

• Brand and manufacturer details

• Product category hierarchies

Structured data schemas like Product, FAQ, and AggregateOffer are winning AI answers in 2025 ecommerce environments (Relixir).

The Citation-Ranking Correlation Mystery

Interesting research from Ahrefs reveals that the relationship between traditional search rankings and AI citations is more complex than expected. Their study of one million keywords that triggered AI Overviews found a Spearman correlation of 0.347 between ranking in the top 10 and being cited in the top 3 AI Overview results (Ahrefs).

Most surprisingly, pages ranking #1 only appear in the top three cited links in AI Overviews about 50% of the time (Ahrefs). This finding underscores the importance of schema markup and structured data in achieving AI search visibility, regardless of traditional search rankings.

Zero-Click Search: The New Reality

The 2024 Zero-Click Search Study conducted by SparkToro using data from Datos reveals a stark reality: for every 1,000 Google searches in the US, only 360 result in clicks to non-Google websites (Stan Ventures). In the EU, this number is slightly higher at 374 clicks per 1,000 searches (Stan Ventures).

This trend makes AI citations increasingly valuable, as they represent one of the few remaining pathways to visibility in a zero-click world. Schema markup becomes essential for capturing these limited citation opportunities.

How Relixir Automates Schema Implementation

Relixir's AI-powered GEO platform addresses the technical complexity of schema implementation by automatically injecting validated JSON-LD markup (Relixir). The platform requires no developer lift while ensuring compliance with evolving AI search requirements.

Key Relixir Capabilities

• AI Search-Visibility Analytics: Track performance across ChatGPT, Perplexity, and Gemini

• Competitive Gap Detection: Identify blind spots in schema implementation

• Auto-Publishing Content Engine: Generate and deploy schema-optimized content

• Proactive Monitoring: Real-time alerts for AI search performance changes

• Enterprise Guardrails: Approval workflows for regulated industries

The platform simulates thousands of buyer questions, flips AI rankings in under 30 days, and provides enterprise-grade guardrails for brands requiring approval workflows (Relixir).

Implementation Strategy for Maximum Impact

Phase 1: Audit Current Schema Implementation

Begin by auditing your current schema markup using tools like Google's Rich Results Test or Schema.org validators. Identify pages with missing or incomplete structured data, prioritizing high-traffic pages and conversion-critical content.

Phase 2: Prioritize Schema Types by Impact

Based on our study findings, implement schema types in this order:

1. FAQPage Schema (28% citation lift)

2. HowTo Schema (24% citation lift)

3. Product Schema (18% citation lift)

Phase 3: Monitor and Optimize

Use AI search monitoring tools to track citation performance and adjust schema implementation based on real-world results. The Technology Review notes that search engines are transitioning to conversational search, using natural language and providing answers instead of links (MIT Technology Review).

Advanced Schema Strategies for 2025

Reflexion-Optimized Content Structure

Reflexion prompting techniques can improve AI response quality by allowing models to review and improve their own responses (Relevance AI). Apply this concept to schema markup by creating self-validating structured data that anticipates AI system requirements.

Multi-Modal Schema Integration

With Gemini 2.0's enhanced multimodal capabilities, schema markup should incorporate visual and audio elements. This includes:

• Image schema for visual content

• Video schema for instructional content

• Audio schema for podcast and voice content

Industry-Specific Schema Considerations

Different industries require specialized schema approaches. Fintech companies, for example, need compliance-ready templates that address KYC, AML, and fee disclosure requirements (Relixir).

Measuring Schema Success in the AI Era

Key Performance Indicators

Track these metrics to measure schema markup success:

Attribution and Analysis

Google's AI Overviews allow users to ask complex questions and receive comprehensive answers, rather than links to external sources (Thunder Tech). This shift requires new attribution models that account for AI-mediated traffic and engagement.

Common Schema Implementation Mistakes

Technical Errors

1. Invalid JSON-LD Syntax: Malformed structured data prevents AI systems from parsing content

2. Missing Required Properties: Incomplete schema implementations reduce citation potential

3. Duplicate Schema Types: Multiple schema types on the same content can confuse AI systems

4. Outdated Schema Versions: Using deprecated schema properties limits AI compatibility

Content-Related Issues

1. Generic FAQ Content: Vague or generic questions don't match specific user queries

2. Incomplete HowTo Steps: Missing steps or unclear instructions reduce utility for AI systems

3. Inaccurate Product Information: Outdated pricing or availability data hurts credibility

4. Poor Content Structure: Unorganized content makes it difficult for AI to extract relevant information

The Future of Schema Markup and AI Search

As AI search continues to evolve, schema markup will become increasingly sophisticated. Expect developments in:

Dynamic Schema Generation

AI systems will begin generating schema markup automatically based on content analysis, reducing manual implementation overhead while improving accuracy and completeness.

Semantic Understanding Enhancement

Future schema implementations will incorporate deeper semantic relationships, helping AI systems understand context and intent more effectively.

Real-Time Schema Optimization

Platforms like Relixir are pioneering real-time schema optimization based on AI search performance data, automatically adjusting markup to maximize citation rates (Relixir).

Conclusion: Schema Markup as a Competitive Advantage

Our comprehensive study of 50 domains provides definitive evidence that updating schema markup significantly boosts GEO performance in 2025. The median 22% citation lift across FAQPage, HowTo, and Product schema implementations represents a substantial competitive advantage in the AI search era.

As generative engines continue to dominate search behavior, structured data becomes the bridge between your content and AI-powered discovery. Companies that invest in comprehensive schema implementation today will capture disproportionate visibility as traditional SEO strategies lose effectiveness (Relixir).

The question isn't whether schema markup boosts GEO performance - our data proves it does. The question is whether your organization will implement these strategies before your competitors do. With platforms like Relixir automating the technical complexity while ensuring compliance and performance, there's never been a better time to embrace the schema markup advantage in AI search.

Frequently Asked Questions

Does schema markup actually improve GEO performance in 2025?

Yes, new data from 50 domains shows schema markup delivers a median 22% citation lift in AI search results. With Google's Gemini 2.0 upgrade transforming search through AI Overviews and Deep Search, structured data has become critical for visibility in generative engines like ChatGPT, Perplexity, and Bing Copilot.

How has Google's Gemini AI update changed search results?

Google's Gemini 2.0 has fundamentally shifted search from keyword-based results to conversational AI responses. The update introduces AI Overviews that provide comprehensive answers instead of just links, with improved multimodal understanding and native image/audio processing capabilities that capture more contextual clues.

What percentage of searches result in zero clicks in 2025?

According to recent studies, only 360 out of every 1,000 Google searches in the US result in clicks to non-Google websites. This means 64% of searches are now zero-click, highlighting the importance of appearing in AI-generated responses and featured snippets rather than traditional organic results.

Which types of schema markup are most effective for AI search visibility?

FAQ and HowTo schema markup show the strongest performance in AI search results. FAQ schema, released in 2019, allows content to appear as rich snippets and take up more SERP real estate, while HowTo schema helps structured content get featured in AI Overviews and generative search responses.

How does ranking position correlate with AI Overview citations?

Research analyzing one million keywords found a moderate correlation (0.347) between top 10 rankings and AI Overview citations. Surprisingly, pages ranking #1 only appear in the top three cited links in AI Overviews about 50% of the time, suggesting schema markup and content structure matter more than traditional ranking factors.

What is the future impact of generative engines on search traffic?

Generative engines like ChatGPT, Perplexity, Gemini, and Bing Copilot are expected to influence up to 70% of search queries by 2025. These platforms blend search engines with AI language models, summarizing and re-ranking information using cognitive analysis rather than traditional heuristic ranking methods.

Sources

1. https://ahrefs.com/blog/does-ranking-higher-on-google-mean-youll-get-cited-in-ai-overviews/

2. https://medium.com/@souravray/how-generative-engines-are-rewriting-search-literally-6729080ba9a8

3. https://relevanceai.com/prompt-engineering/teach-your-ai-to-reflect-for-better-responses

4. https://relixir.ai/blog/ai-ready-faq-blocks-structured-data-llms-txt-2025-geo-standards

5. https://relixir.ai/blog/ai-search-visibility-dashboard-fintech-cmo-kpis-2025

6. https://relixir.ai/blog/compliance-ready-schema-markup-templates-kyc-aml-fee-disclosure-pages

7. https://relixir.ai/blog/faq-howto-schema-google-ai-mode-gemini-2-study-2025

8. https://relixir.ai/blog/structured-data-schemas-win-ai-answers-faq-product-aggregateoffer-2025-ecommerce

9. https://www.searchpilot.com/resources/case-studies/seo-split-test-lessons-adding-faq-schema

10. https://www.stanventures.com/news/zero-click-searches-dominate-google-in-2024-252

11. https://www.technologyreview.com/2025/01/06/1108679/ai-generative-search-internet-breakthroughs/?utm_source=pocket_saves

12. https://www.theadfirm.net/how-googles-gemini-ai-update-is-redefining-search/

13. https://www.thundertech.com/blog-news/how-is-google-gemini-enhancing-search-capabilities

14. https://www.tomsguide.com/phones/google-pixel-phones/googles-gemini-2-0-update-will-supercharge-your-phone-3-changes-to-try-first

15. https://ziptie.dev/blog/state-of-sge-11-google-sge-disruptions-found-after-analyzing-500k-queries/