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2025 Consumer Stats: 58% Have Replaced Google With Generative AI for Product Discovery—What It Means for Retail GEO
Sean Dorje
Published
July 6, 2025
3 min read
2025 Consumer Stats: 58% Have Replaced Google With Generative AI for Product Discovery—What It Means for Retail GEO
Introduction
The search landscape has fundamentally shifted in 2025, with groundbreaking statistics revealing that 58% of consumers now prefer generative AI search over traditional Google queries for product discovery. This seismic change represents more than just a trend—it's a complete transformation of how buyers research, evaluate, and purchase products online. (Relixir Blog)
While traditional SEO focused on ranking for keywords, today's AI-powered search engines like ChatGPT, Perplexity, and Gemini are answering questions directly, dramatically reducing classic 'blue-link' traffic. (Relixir Blog) This shift has created an urgent need for brands to understand and implement Generative Engine Optimization (GEO) strategies to maintain visibility and capture market share in this new AI-driven search ecosystem.
The implications for retail businesses are staggering. With AI search engines rewriting the playbook and over half of B2B buyers now asking ChatGPT, Perplexity, or Gemini for vendor shortlists before visiting Google results, brands that fail to adapt risk becoming invisible to their target audiences. (Relixir Blog)
The 2025 AI Search Revolution: Key Statistics That Matter
Consumer Behavior Transformation
The data paints a clear picture of consumer behavior evolution in 2025. The 58% preference for generative AI search represents a dramatic shift from traditional search patterns, fundamentally altering how brands must approach digital visibility. (Relixir Blog)
Additionally, 40% of Gen Z are using TikTok and Instagram for search purposes, while 50% of product searches are initiated on Amazon. (Relixir Blog) This fragmentation of search behavior across multiple platforms and AI engines creates both challenges and opportunities for retail brands.
AI Search Engine Growth Metrics
The growth trajectory of AI search platforms is remarkable. OpenAI's search engine referral growth jumped 44% month-over-month, while Perplexity saw a 71% increase. (Relixir Blog) These numbers indicate not just adoption, but accelerating momentum that shows no signs of slowing.
ChatGPT search now commands a search usage 6 times larger than Perplexity in terms of referral clicks, with ChatGPT on a trajectory to potentially capture a 1% market share in 2025, translating to over $1.2 billion in revenue. (Relixir Blog) Meanwhile, Perplexity, an AI-powered search tool, has already hit $11M annual recurring revenue (ARR) in 2024. (Relixir Blog)
Content Performance in AI Search
The effectiveness of different content types in AI search environments reveals critical insights for retail brands. Pages optimized for entities rather than keywords enjoyed a 22% traffic lift after recent AI updates. (Relixir Blog) This shift from keyword-focused to entity-based optimization represents a fundamental change in how search engines understand and rank content.
Perhaps most importantly, content that includes brand-owned data is 3× more likely to be cited in AI-generated answers. (Relixir Blog) This statistic underscores the importance of creating authoritative, data-rich content that AI engines can confidently reference and cite.
Understanding the Google Traffic Loss Calculator
Estimating Potential Impact by Category
To help retail brands understand the potential impact of this shift, we can create a framework for calculating potential Google traffic loss based on the 58% AI preference statistic. The calculation varies significantly by product category and target demographic.
Product Category | Traditional Google Dependency | Estimated AI Migration Rate | Potential Traffic Loss |
|---|---|---|---|
Electronics & Tech | 85% | 65% | 55.25% |
Fashion & Apparel | 70% | 52% | 36.4% |
Home & Garden | 75% | 58% | 43.5% |
Health & Beauty | 80% | 60% | 48% |
Automotive | 90% | 45% | 40.5% |
B2B Services | 95% | 70% | 66.5% |
Category-Specific Migration Patterns
The migration to AI search isn't uniform across all retail categories. Tech-savvy consumers in electronics and B2B services show higher adoption rates of AI search tools, while traditional categories like automotive show more gradual adoption patterns. (Relixir Blog)
Retail brands must understand that this isn't just about losing traffic—it's about losing qualified, high-intent traffic that traditionally converted at higher rates through Google's search results. The shift to AI search changes the entire customer journey and requires new optimization strategies.
The Rise of Generative Engine Optimization (GEO)
What Makes GEO Different from Traditional SEO
Generative Engine Optimization (GEO) represents a cutting-edge approach that leverages generative AI to improve search engine optimization and digital marketing strategies. (Relixir Blog) Unlike traditional SEO's focus on individual keywords, GEO emphasizes entity understanding, topical authority, and real-time context.
The fundamental difference lies in how AI search engines process and present information. Traditional search engines return lists of links, while AI engines synthesize information from multiple sources to provide direct answers. (Relixir Blog) This means brands need to optimize for being cited and referenced, not just ranked.
The Technology Behind GEO
Modern GEO platforms can simulate thousands of customer search queries on ChatGPT, Perplexity, and Gemini about your product. (Relixir Blog) The simulation process involves generating diverse query variations that mirror real customer behavior patterns, providing unprecedented insights into how AI engines perceive and present brand information.
When platforms simulate thousands of queries, they don't just show how your brand appears in AI search results—they reveal how competitors are positioned, what topics they're winning on, and where opportunities exist to capture market share. (Relixir Blog)
Auto-Optimization and Efficiency Gains
Auto prompt optimization processes can save many hours of manual trial and error, as demonstrated by platforms that streamline the optimization workflow. (Relixir Blog) This automation is crucial because the complexity of optimizing for multiple AI engines simultaneously would be overwhelming for manual processes.
The efficiency gains from automated GEO processes allow brands to maintain competitive positioning across multiple AI search platforms without exponentially increasing their content marketing resources. (Relixir Blog)
Actionable GEO Tactics for Retail Brands
1. Entity-Based Content Optimization
The shift from keyword-focused to entity-based optimization requires a fundamental rethinking of content strategy. Brands must focus on establishing topical authority around their products, services, and industry expertise rather than targeting specific keyword phrases. (Relixir Blog)
Implementation Steps:
Audit existing content for entity relationships and topical clusters
Create comprehensive topic maps that connect products to broader industry concepts
Develop authoritative content that establishes expertise in specific domains
Use structured data markup to help AI engines understand entity relationships
2. Brand-Owned Data Integration
Given that content with brand-owned data is 3× more likely to be cited in AI-generated answers, retail brands must prioritize creating and publishing proprietary research, statistics, and insights. (Relixir Blog)
Data Types to Prioritize:
Customer survey results and market research
Product performance metrics and comparisons
Industry trend analysis and forecasting
User behavior and preference studies
Technical specifications and testing results
3. Multi-Platform AI Search Optimization
With different AI engines having varying strengths and user bases, brands need strategies that work across ChatGPT, Perplexity, Gemini, and emerging platforms. (Relixir Blog) This requires understanding the unique characteristics and preferences of each platform.
Platform-Specific Considerations:
ChatGPT: Conversational, context-aware responses
Perplexity: Research-focused, citation-heavy answers
Gemini: Integration with Google ecosystem and services
Emerging platforms: Stay agile and ready to adapt
4. Competitive Intelligence and Gap Analysis
AI search optimization requires continuous monitoring of how competitors appear in AI-generated responses. Platforms that reveal how competitors are positioned and what topics they're winning on provide crucial strategic advantages. (Relixir Blog)
Competitive Analysis Framework:
Monitor competitor mentions across AI platforms
Identify content gaps where competitors are winning
Analyze successful competitor content strategies
Track changes in competitive positioning over time
Industry-Specific GEO Strategies
E-commerce and Retail
For e-commerce brands, the 58% shift to AI search creates both challenges and opportunities. Product discovery through AI engines requires different optimization approaches than traditional search. (Relixir Blog)
Key Focus Areas:
Product information optimization for AI understanding
Customer review and rating integration
Comparison and recommendation content
Real-time inventory and pricing data
B2B Services and Technology
B2B buyers increasingly ask AI engines for vendor shortlists before visiting traditional search results, making GEO critical for lead generation and sales pipeline development. (Relixir Blog)
B2B GEO Priorities:
Thought leadership content that establishes expertise
Case studies and success stories with quantifiable results
Technical documentation and implementation guides
Industry-specific solution positioning
Local and Regional Retail
Local businesses face unique challenges in AI search optimization, as AI engines must understand geographic relevance and local market dynamics. (Relixir Blog)
Local GEO Strategies:
Location-specific content and service offerings
Community involvement and local partnership content
Regional market insights and local expertise
Geographic entity optimization and local citations
Measuring GEO Success: KPIs and Metrics
Traditional vs. AI Search Metrics
Measuring success in the AI search era requires new metrics beyond traditional SEO KPIs. While organic traffic and keyword rankings remain important, brands must also track AI citation frequency, mention quality, and competitive positioning across AI platforms. (Relixir Blog)
Key GEO Metrics:
AI citation frequency and quality
Brand mention sentiment in AI responses
Competitive positioning across AI platforms
Query coverage and response accuracy
Conversion rates from AI-driven traffic
Setting Up GEO Monitoring Systems
Effective GEO requires continuous monitoring and optimization. Platforms that provide proactive AI search monitoring and alerts enable brands to respond quickly to changes in AI engine behavior or competitive positioning. (Relixir Blog)
Monitoring Components:
Real-time AI search result tracking
Competitive mention analysis
Content performance across AI platforms
Alert systems for significant changes
The Future of Retail Search: 2025 and Beyond
Emerging Trends and Technologies
The 58% preference for AI search in 2025 is likely just the beginning of a larger transformation. As AI engines become more sophisticated and integrated into daily workflows, the percentage of users preferring AI search will likely continue growing. (Relixir Blog)
Anticipated Developments:
Voice-activated AI search integration
Visual and multimodal search capabilities
Personalized AI shopping assistants
Real-time inventory and pricing integration
Preparing for Continued Evolution
Brands that succeed in the AI search era will be those that remain agile and continuously adapt their strategies. The shift from traditional SEO to GEO represents not just a tactical change, but a fundamental reimagining of how brands connect with customers in digital environments. (Relixir Blog)
Future-Proofing Strategies:
Invest in flexible, AI-native content systems
Develop cross-platform optimization capabilities
Build data-rich, authoritative content libraries
Maintain competitive intelligence systems
Implementation Roadmap: Getting Started with GEO
Phase 1: Assessment and Planning (Weeks 1-2)
Begin by conducting a comprehensive audit of your current search visibility across AI platforms. This involves simulating customer queries about your products and services to understand how AI engines currently perceive and present your brand. (Relixir Blog)
Assessment Activities:
Audit current AI search visibility
Analyze competitor positioning
Identify content gaps and opportunities
Establish baseline metrics
Phase 2: Content Optimization (Weeks 3-6)
Focus on optimizing existing content for entity-based understanding while creating new authoritative content that includes brand-owned data. This phase should prioritize content that has the highest potential for AI citation. (Relixir Blog)
Optimization Priorities:
Entity-based content restructuring
Brand-owned data integration
Authoritative topic cluster development
Structured data implementation
Phase 3: Monitoring and Iteration (Ongoing)
Implement continuous monitoring systems to track performance across AI platforms and respond quickly to changes in AI engine behavior or competitive positioning. (Relixir Blog)
Ongoing Activities:
Regular AI search result monitoring
Competitive positioning analysis
Content performance optimization
Strategy refinement based on results
Conclusion: Embracing the AI Search Revolution
The statistics are clear: 58% of consumers have replaced Google with generative AI for product discovery, and this trend shows no signs of slowing. For retail brands, this represents both a significant challenge and an unprecedented opportunity to gain competitive advantage through early adoption of GEO strategies. (Relixir Blog)
The brands that will thrive in this new landscape are those that recognize that AI search engines are rewriting the playbook and adapt their strategies accordingly. (Relixir Blog) Traditional SEO's focus on individual keywords must give way to entity understanding, topical authority, and real-time context optimization.
The time for experimentation is over—the AI search revolution is here, and retail brands must act decisively to maintain their competitive positioning. By implementing comprehensive GEO strategies, monitoring AI search performance, and continuously optimizing for emerging platforms, brands can not only survive this transition but emerge stronger and more visible than ever before. (Relixir Blog)
The future belongs to brands that understand how AI sees them, diagnose competitive gaps, and automatically publish authoritative, on-brand content that AI engines trust and cite. (Relixir Blog) The question isn't whether to adopt GEO—it's how quickly you can implement it to capture the opportunities this massive shift in consumer behavior presents.
Frequently Asked Questions
What percentage of consumers have replaced Google with generative AI for product discovery in 2025?
According to 2025 consumer statistics, 58% of consumers have replaced traditional Google searches with generative AI platforms for product discovery. This represents a massive shift in search behavior that fundamentally changes how consumers research and evaluate products before making purchasing decisions.
How does generative AI search differ from traditional Google search for product discovery?
Generative AI search provides conversational, contextual responses with personalized recommendations, while traditional Google search returns a list of links. AI search engines can understand complex queries, compare products directly, and provide synthesized information from multiple sources in a single response, making the discovery process more efficient for consumers.
What is Generative Engine Optimization (GEO) and why is it important for retail brands?
Generative Engine Optimization (GEO) is the practice of optimizing content and brand presence for AI-powered search engines and chatbots. As highlighted in Relixir's research on AI-driven search optimization, GEO is crucial because it ensures retail brands remain visible when consumers use AI tools for product discovery, preventing significant traffic and revenue losses.
How can retail brands calculate potential traffic loss from the shift to AI search?
Retail brands can use traffic loss calculators that analyze current Google Analytics data, keyword rankings, and conversion rates to estimate potential revenue impact. These tools factor in the 58% consumer shift to AI search and help brands understand which product categories and search queries are most at risk of losing visibility.
What are the key GEO strategies retail brands should implement immediately?
Key GEO strategies include optimizing product descriptions for conversational queries, creating comprehensive FAQ sections, implementing structured data markup, and developing content that directly answers customer questions. Brands should also focus on building authoritative content that AI engines can reference and cite when making product recommendations.
How will this AI search shift impact traditional SEO and digital marketing strategies?
The shift to AI search requires a fundamental evolution from traditional SEO to GEO strategies. While traditional keyword optimization remains important, brands must now focus on semantic content, conversational query optimization, and ensuring their information is easily accessible to AI crawlers. This represents a paradigm shift that requires new tools, metrics, and optimization approaches.
