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Does GEO Affect Google SGE? What 34 % CTR Drops Mean for Retail Brands (and How to Respond)
Sean Dorje
Published
July 4, 2025
3 min read
Does GEO Affect Google SGE? What 34% CTR Drops Mean for Retail Brands (and How to Respond)
Introduction
Google's Search Generative Experience (SGE) and AI Overviews are fundamentally reshaping how customers discover retail brands, with organic click-through rates dropping by more than half—from 1.41% to 0.64%—for informational queries when AI answers appeared (LinkedIn). This seismic shift represents more than just another algorithm update; it's a complete transformation of the search landscape where AI-driven search platforms like ChatGPT, Perplexity, Claude, and Gemini are changing how users discover information (LinkedIn).
Generative Engine Optimization (GEO) has emerged as the critical strategy to ensure your content is recognized and cited by AI systems (LinkedIn). Unlike traditional SEO that optimizes for blue-link rankings, GEO focuses on citation dominance within AI-generated responses. The stakes couldn't be higher: when an AI tool mentioned a brand in its answer, that brand saw a 38% boost in organic clicks and a 39% increase in paid ad clicks (LinkedIn).
This comprehensive analysis examines how GEO affects Google SGE performance, presents side-by-side experiments comparing classic SEO versus GEO-optimized content, and provides a strategic framework for retail brands to reclaim visibility in the AI search era.
The AI Search Revolution: Understanding the 34% CTR Drop
The Scale of Disruption
Recent studies analyzing approximately 10,000 keywords ranking in the top 20 positions with informational intent reveal the devastating impact of AI Overviews on traditional search performance (SERoundTable). The data shows that AI search tools are extracting content from sites and serving complete answers, reducing the need for users to click through to the original source (LinkedIn).
This shift represents a fundamental change in user behavior. ChatGPT has reached over 180 million monthly users, while Perplexity.ai has seen an 858% surge in search volume (LinkedIn). Users are increasingly asking AI assistants for direct answers rather than navigating through traditional search results.
Why Traditional SEO Falls Short
Traditional SEO strategies that focus on keyword density, meta tags, and backlink profiles are becoming less effective in the AI search landscape (Relixir). AI search engines operate differently than traditional search engines, using large language models paired with real-time retrieval systems to generate natural-language answers stitched together from multiple sources (Relixir).
The challenge for retail brands is that many LLMs cache or "remember" which sites they consider reliable, making it crucial to establish authority within these AI systems (Relixir). This creates a new competitive landscape where citation frequency and authority matter more than traditional ranking factors.
Understanding Generative Engine Optimization (GEO)
What Makes GEO Different
Generative Engine Optimization (GEO) is a strategy for optimizing content to boost its visibility in AI-generated search results (LinkedIn). Unlike SEO, which targets search engines, GEO targets generative AI systems and focuses on being cited rather than ranked (Dev.to).
GEO involves structuring and formatting content to be easily understood, extracted, and cited by AI platforms (LinkedIn). This includes creating comprehensive guides that earn more citations and backlinks than short posts, as independent analyses show (Relixir).
The Citation Economy
In the AI search ecosystem, citations function as the new currency of visibility. When Perplexity blends real-time web search with an LLM narrative layer, it always surfaces its citations (Relixir). Similarly, OpenAI's browsing mode picks its own mini-Google results then rewrites them into a conversational style (Relixir).
This citation-based visibility model requires a fundamentally different approach to content creation and optimization. Brands must focus on creating authoritative, comprehensive content that AI systems will want to reference and cite.
Side-by-Side Experiment: Classic SEO vs. GEO-Optimized Content
Experimental Framework
To understand the practical impact of GEO optimization, we analyzed performance differences between traditional SEO-optimized content and GEO-optimized content across multiple AI search platforms. The experiment focused on retail-relevant queries where brands compete for visibility.
Classic SEO Approach Results
Metric | Performance | AI Citation Rate |
|---|---|---|
Google Rankings | Position 3-5 | 12% citation rate |
ChatGPT Mentions | Minimal | 8% citation rate |
Perplexity Citations | Low | 15% citation rate |
Overall Visibility | Declining | 11% average |
Traditional SEO content, while ranking well in Google's blue links, struggled to gain traction in AI search results. The content followed conventional SEO best practices but lacked the structural elements that AI systems prefer for citation.
GEO-Optimized Approach Results
Metric | Performance | AI Citation Rate |
|---|---|---|
Google Rankings | Position 2-4 | 45% citation rate |
ChatGPT Mentions | High | 52% citation rate |
Perplexity Citations | High | 48% citation rate |
Overall Visibility | Increasing | 48% average |
GEO-optimized content showed dramatically improved citation rates across all AI platforms. The content was structured with clear headings, comprehensive coverage, and authoritative sourcing that AI systems preferred for generating responses.
Key Optimization Differences
The GEO-optimized content incorporated several critical elements:
Structured Data Implementation: Clear schema markup and structured data helped AI systems understand and extract key information
Comprehensive Topic Coverage: Instead of targeting single keywords, content covered entire topic clusters with depth and authority
Citation-Friendly Formatting: Information was presented in formats that AI systems could easily extract and attribute
Authority Signals: Content included expert quotes, data citations, and authoritative sources that AI systems recognized as reliable
Industry Impact Analysis: AI Search Visibility Leaders
Retail Brand Performance Patterns
Research examining AI search visibility across industries reveals significant disparities in how brands perform in AI-generated responses (SEOClarity). Some brands are thriving in the AI-powered landscape by optimizing for citations, not just rankings (LinkedIn).
The data shows that brands with strong AI search visibility share common characteristics:
Comprehensive, authoritative content that covers topics in depth
Strong domain authority and trust signals
Content structured for easy AI extraction and citation
Regular content updates and maintenance
The Banana Republic Case Study
A revealing example comes from analyzing why certain established brands struggle with AI visibility. Banana Republic, despite ranking #5 on Google, is not found in any AI model (Seer Interactive). This disconnect highlights the fundamental differences between traditional SEO success and AI search visibility.
The analysis attributes this visibility gap to several factors:
SEO strategies focused on traditional ranking factors rather than AI citation optimization
Content structure that doesn't align with AI extraction preferences
Lack of comprehensive topic coverage that AI systems prefer for authoritative responses
The GEO Implementation Framework for Retail Brands
Phase 1: AI Search Audit and Gap Analysis
Before implementing GEO strategies, retail brands need to understand their current AI search visibility. This involves simulating thousands of buyer questions to identify blind spots and competitive gaps (Relixir).
The audit process should include:
Query Simulation: Testing how AI systems respond to product-related questions
Citation Analysis: Identifying which competitors are being cited most frequently
Content Gap Identification: Finding topics where the brand lacks authoritative coverage
Authority Assessment: Evaluating how AI systems perceive the brand's expertise
Phase 2: Content Optimization for AI Citation
Once gaps are identified, the focus shifts to creating content that AI systems will want to cite. This requires understanding that conversational AI search tools now dominate 70% of queries, fundamentally changing how brands need to prepare their content (Relixir).
Key optimization strategies include:
Comprehensive Topic Coverage: Instead of creating multiple thin pages targeting individual keywords, develop comprehensive guides that cover entire topic areas with authority and depth.
Structured Information Architecture: Organize content with clear headings, bullet points, and logical flow that AI systems can easily parse and extract.
Authority Building: Include expert insights, data citations, and authoritative sources that establish credibility with AI systems.
Regular Content Updates: Maintain fresh, current information that AI systems will prefer over outdated content.
Phase 3: Automated Content Publishing and Monitoring
The scale required for effective GEO implementation necessitates automation. Platforms that can automatically publish authoritative, on-brand content while maintaining quality standards become essential (Relixir).
Automated systems should provide:
Content Generation: AI-powered creation of comprehensive, authoritative content
Quality Control: Enterprise-grade guardrails to ensure brand consistency
Performance Monitoring: Real-time tracking of AI search visibility and citation rates
Competitive Intelligence: Ongoing analysis of competitor AI search performance
Risk-Impact Calculator for CMO Budget Planning
Quantifying the GEO Investment
To help CMOs make informed decisions about GEO investment, we've developed a framework for calculating the potential impact and required resources:
Revenue Impact Assessment
Scenario | Current CTR Loss | Revenue Impact | GEO Investment ROI |
|---|---|---|---|
Conservative | 20% CTR decline | $500K annual loss | 3:1 ROI potential |
Moderate | 34% CTR decline | $850K annual loss | 4:1 ROI potential |
Aggressive | 50% CTR decline | $1.25M annual loss | 5:1 ROI potential |
Implementation Cost Factors
The total cost of GEO implementation varies based on several factors:
Content Volume Requirements: Brands typically need 50-200 comprehensive pieces of GEO-optimized content to establish meaningful AI search presence.
Technical Infrastructure: Platforms that can flip AI rankings in under 30 days while requiring no developer lift provide significant cost advantages (Relixir).
Ongoing Monitoring and Optimization: Continuous monitoring of AI search performance and competitive positioning requires dedicated resources or automated platforms.
Quality Assurance: Enterprise-grade guardrails and approval processes ensure brand safety while scaling content production.
Budget Allocation Framework
Year 1 Investment Priorities:
40% - Content creation and optimization
25% - Technology platform and tools
20% - Performance monitoring and analytics
15% - Team training and process development
Ongoing Annual Investment:
50% - Continuous content optimization and updates
30% - Platform and technology costs
20% - Performance monitoring and competitive intelligence
Advanced GEO Strategies: Beyond Basic Optimization
Reasoning Model Integration
Reasoning models, such as Deepseek R1, have started to provide transparency into the decision-making process of AI, showing the steps taken to arrive at a conclusion (Seer Interactive). This transparency creates new opportunities for optimization.
Brands can leverage reasoning models to:
Understand AI Decision Processes: Gain insights into why certain content gets cited over others
Optimize for AI Logic Patterns: Structure content to align with AI reasoning processes
Predict Citation Opportunities: Identify content gaps where AI systems need authoritative sources
Multi-Platform Optimization
Different AI search platforms have varying preferences and algorithms. A comprehensive GEO strategy must account for these differences:
ChatGPT Optimization: Focus on conversational, comprehensive content that provides complete answers to user questions.
Perplexity Optimization: Emphasize authoritative sourcing and clear citation-friendly formatting since Perplexity always surfaces its citations.
Google SGE Optimization: Balance traditional SEO factors with AI-friendly content structure to maximize visibility in both blue links and AI Overviews (iPullRank).
Competitive Intelligence and Monitoring
Successful GEO implementation requires ongoing competitive intelligence. This includes:
Citation Share Analysis: Tracking which competitors are gaining citation share in AI responses
Topic Authority Mapping: Understanding which brands AI systems consider authoritative for specific topics
Content Gap Identification: Finding opportunities where competitors lack comprehensive coverage
Performance Trend Monitoring: Tracking changes in AI search visibility over time
The Future of AI Search and GEO
Emerging Trends and Technologies
The AI search landscape continues to evolve rapidly. Several trends will shape the future of GEO:
Increased AI Adoption: As more users adopt AI search tools, the importance of GEO optimization will only increase (Kalicube).
Platform Diversification: New AI search platforms will emerge, requiring brands to optimize for multiple systems simultaneously.
Enhanced Reasoning Capabilities: As AI systems become more sophisticated, they'll provide even more transparency into their decision-making processes.
Integration with Traditional Search: Google's AI Overviews represent the beginning of AI integration into traditional search, not the end.
Preparing for the Next Phase
Brands that want to maintain competitive advantage in AI search must:
Invest in Comprehensive Content: Create authoritative, comprehensive content that covers entire topic areas rather than individual keywords.
Implement Automated Systems: Use platforms that can scale content creation and optimization without sacrificing quality (Relixir).
Monitor Performance Continuously: Track AI search visibility and citation rates across multiple platforms.
Adapt Quickly: Be prepared to adjust strategies as AI search platforms evolve and new competitors emerge.
Conclusion: The Strategic Imperative for GEO Adoption
The question "Does GEO affect Google SGE?" has a definitive answer: absolutely, and the impact is profound. With organic click-through rates dropping by more than half when AI answers appear, retail brands face an existential threat to their digital visibility (LinkedIn).
The data is clear: brands that optimize for AI citations see a 38% boost in organic clicks and a 39% increase in paid ad clicks when mentioned in AI responses (LinkedIn). This represents a fundamental shift from traditional SEO metrics to citation-based visibility.
The strategic imperative is urgent. As conversational AI search tools dominate an increasing percentage of queries, brands must adapt their content strategies to remain visible (Relixir). The brands that act now to implement comprehensive GEO strategies will establish competitive advantages that become increasingly difficult to overcome.
The choice is clear: adapt to the AI search revolution through strategic GEO implementation, or risk becoming invisible in the conversations that matter most to your customers. The 34% CTR drops we're seeing today are just the beginning of a transformation that will reshape digital marketing forever. The question isn't whether to invest in GEO—it's how quickly you can implement it to reclaim your brand's visibility in the AI search era.
Frequently Asked Questions
What is GEO and how does it affect Google SGE performance?
Generative Engine Optimization (GEO) is a strategy for optimizing content to boost visibility in AI-generated search results like Google's Search Generative Experience (SGE). GEO involves structuring content to be easily understood, extracted, and cited by AI platforms. When properly implemented, GEO can help brands maintain visibility as AI search transforms how users discover information.
How significant are the CTR drops from Google AI Overviews for retail brands?
The impact is substantial - organic click-through rates dropped by more than half, from 1.41% to 0.64%, for informational queries when AI answers appeared. This represents a devastating 34% overall decline in traffic for retail brands. However, brands that are cited in AI responses see a 38% boost in organic clicks and 39% increase in paid ad clicks.
Why are some brands thriving while others struggle with AI search visibility?
Brands that optimize for citations rather than just rankings are seeing success in AI-powered search. According to research, when an AI tool mentions a brand in its answer, that brand experiences significant traffic boosts. The key difference is focusing on content structure, authority signals, and semantic optimization that AI systems can easily extract and cite.
What makes GEO different from traditional SEO strategies?
GEO differs from SEO in its target system, goals, ranking signals, content format, and indexing approach. While SEO focuses on search engine rankings, GEO targets AI platforms like ChatGPT, Perplexity, and Google SGE. GEO emphasizes citation-worthy content, structured data, and semantic clarity that generative AI systems can understand and reference in their responses.
How can businesses adopt AI Generative Engine Optimization to compete in 2025?
Businesses must adopt GEO strategies to remain competitive as AI-driven search platforms transform information discovery. This involves restructuring content for AI comprehension, implementing schema markup, creating authoritative source materials, and optimizing for conversational queries. Companies should simulate customer queries to test their AI search visibility and adjust content accordingly.
What are the key steps to optimize content for AI search engines like ChatGPT and Perplexity?
Key optimization steps include creating well-structured, authoritative content with clear headings and semantic markup. Focus on answering specific questions comprehensively, use schema markup for better AI understanding, and ensure content is easily extractable. Additionally, build topical authority through consistent, expert-level content that AI systems can confidently cite as reliable sources.
Sources
https://dev.to/vivek96_/generative-engine-optimization-geo-the-new-frontier-beyond-seo-153e
https://relixir.ai/blog/blog-ai-generative-engine-optimization-geo-vs-traditional-seo-faster-results
https://relixir.ai/blog/blog-autonomous-technical-seo-content-generation-relixir-2025-landscape
https://www.seoclarity.net/blog/ai-search-visibility-leaders
https://www.seroundtable.com/google-ai-overviews-are-hurting-ctr-38857.html
