SEO vs AI Presence: The Complete Guide to Dominating Both Google and ChatGPT
A data-driven analysis of how search results differ between traditional search engines and AI chatbots—and what it means for your brand strategy
Introduction: The New Search Landscape
The way people find information is fundamentally changing. While Google processes over 8.5 billion searches per day, ChatGPT has rapidly grown to over 200 million weekly active users asking questions, seeking recommendations, and making decisions.
This isn't a replacement story—it's an evolution story. Both platforms serve different needs, deliver information differently, and create distinct opportunities (and challenges) for brands.
The Critical Question:
How do search results actually differ between Google and ChatGPT, and what does this mean for your content strategy?
We tested 3 real running shoe queries across both platforms, captured screenshots, and analyzed every brand mention, source citation, and structural difference to find out.
Methodology: How We Tested
We tested three real user queries from actual search behavior. These transactional queries represent different levels of specificity and constraints that real shoppers use when researching running shoes.
| Query | Constraints | Complexity |
|---|---|---|
| "female running shoes under $150" | Gender, budget, surface | High |
| "best marathon shoe" | Use-case specific | Medium |
| "men's running shoes" | Gender only | Low |
Testing Process:
- Searched on ChatGPT (logged in, January 2026)
- Searched on Google (same queries, same time)
- Captured full-page screenshots of results
- Documented every brand, source, link, and retailer mentioned
- Analyzed structural and strategic differences
- Tracked traffic flow patterns and conversion pathways
These queries represent real search behavior with varying levels of specificity—from broad exploration to highly constrained shopping needs.
Query Analysis: Running Shoe Searches
We tested three real running shoe queries that represent different levels of specificity and constraints that actual shoppers use.
Query 1: Budget-Constrained Female Running Shoes
"What are some reliable female running shoes for road running under 150 USD?"
This query demonstrates high complexity with three constraints: gender, surface type, and budget.
ChatGPT Response:
Google Response:
Summary - ChatGPT:
- • Brands: 10 brands (Brooks, Nike, ASICS, New Balance, Saucony, Mizuno, PUMA, Hoka, On)
- • Products: 11+ models with 3 visual cards
- • Retailers: 1 mentioned (Nike)
- • Links: 0 clickable
- • Traffic: Zero
Summary - Google:
- • AI Overview: ASICS Novablast 5 at $150
- • Sponsored: 6 products from 4 brands
- • Organic: GearLab, RunRepeat
- • Links: 10+ clickable
- • Traffic: Distributed to retailers + editorial
Key Finding:
ChatGPT provided 2.5x more brands (10 vs 4 in Google sponsored), but Google created actual commerce pathways with clickable retailer links and shopping opportunities. ChatGPT = awareness, Google = awareness + conversion.
Query 2: Marathon-Specific Running Shoes
"What is the best shoe for running a marathon?"
This query represents medium complexity—use-case specific but no additional constraints.
ChatGPT Response:
Google Response:
Summary - ChatGPT:
- • Brands: 3 brands (Nike, adidas, Hoka)
- • Products: 5 models (racing vs training)
- • Sources: Runner's World, Women's Health, Triathlete mentioned
- • Links: 0 clickable
- • Traffic: Zero
Summary - Google:
- • AI Overview: 6 brands (Nike, Adidas, ASICS, Saucony, PUMA, Hoka)
- • Sponsored: 6+ visible products
- • Organic: The Run Testers, Runner's World, RunRepeat
- • Links: 10+ clickable
- • Traffic: High potential to retailers + publishers
Key Finding:
Google's AI Overview mentioned 2x more brands (6 vs 3) than ChatGPT's full response. Google also provided multiple traffic pathways while ChatGPT mentioned editorial sources (Runner's World, Triathlete) without linking to them—awareness without attribution traffic.
Query 3: Simple Gender-Specific Request
"Can you recommend me men's running shoes"
This query represents low complexity—broad, gender-only constraint, typical of early research phase.
ChatGPT Response:
Google Response:
Summary - ChatGPT:
- • Brands: 3 brands (Nike, New Balance, adidas)
- • Nike Dominance: 4 of 6 products (67%) were Nike
- • Products: 6 models with 3 visual cards
- • Links: 0 clickable
- • Traffic: Zero
Summary - Google:
- • AI Overview: 3 brands (ASICS, Brooks, Adidas) - balanced
- • Organic: RunRepeat, Runner's World
- • Videos: "The Best & Worst Running Shoes of 2025"
- • Links: 5+ clickable
- • Traffic: Distributed to publishers + video creators
Key Finding:
Despite ChatGPT showing Nike at 67% of recommendations, Google provided more balanced brand coverage with no single brand dominating. Google also drove traffic to diverse content types (editorial, video, community), while ChatGPT kept all engagement in-platform.
Cross-Query Patterns
| Query | ChatGPT Brands | Google AI Overview | Winner |
|---|---|---|---|
| Female shoes under $150 | 10 brands | 1 brand (ASICS) | ChatGPT (diversity) |
| Marathon shoes | 3 brands | 6 brands | Google (2x more) |
| Men's shoes | 3 brands | 3 brands | Tie (Google more balanced) |
The Traffic Reality:
ChatGPT Traffic Model:
User → Query → Answer → Session Ends
Brands Mentioned: ✅ | Traffic Generated: ❌ (zero across all queries)
Google Traffic Model:
User → Query → SERP → Multiple Pathways (Sponsored, Organic, Videos, Shopping)
Brands Mentioned: ✅ | Traffic Generated: ✅ (distributed across ecosystem)
Strategic Insights from Real Queries
📊 Brand Visibility ≠ Traffic
ChatGPT provided more brands in 1 of 3 queries but zero traffic across all. Being mentioned in ChatGPT = awareness without website visits.
💰 Budget Constraint Accuracy
ChatGPT showed products exceeding the $150 budget constraint. Google's sponsored products better aligned with budget filters.
📰 Source Attribution Matters
ChatGPT used editorial content without attribution links. Google credited all sources with dates and traffic opportunities. Publishers benefit from Google, not ChatGPT.
⚖️ Brand Concentration Risk
ChatGPT showed 67% Nike for generic "men's shoes" query. Google's AI Overview more balanced across brands. Diversity matters for competitive brand visibility.
Strategic Implications
For AI Presence
To be mentioned by ChatGPT, you need to be in the training data and recognized as authoritative:
1. Be Part of the Training Data
- • Create authoritative, well-structured content
- • Publish on high-authority domains
- • Contribute to Wikipedia and educational resources
2. Build Brand Recognition
- • Get featured in "best of" lists
- • Generate editorial mentions
- • Win industry awards
3. Focus on Entity Recognition
- • Clear brand definition in knowledge graphs
- • Consistent NAP across the web
- • Structured data markup
4. Emphasize Expertise
- • Demonstrate expertise through content
- • Get cited by authoritative sources
- • Build credentials and awards
For Traditional SEO
To maintain visibility in Google, you need the full SEO toolkit:
Optimize for AI Overviews
AI Overviews now appear on 60%+ of Google searches. Structure content to answer questions clearly and use schema markup.
Maintain Link Ecosystems
Build relationships with review sites and industry publications. Get mentioned in editorial "best of" lists.
Diversify Content Formats
Videos, images, and interactive content are visible in traditional search. YouTube videos rank in Google results.
Leverage Paid Channels
Shopping ads and sponsored placements are exclusive to traditional search. Optimize product feeds and bid competitively.
Action Plan for Brands
1Phase 1: Audit Current Presence
AI Presence Audit:
- Test 10-20 relevant queries in ChatGPT
- Document which queries your brand appears in
- Note competitor mentions
- Identify gaps
SEO Presence Audit:
- Check Google rankings for same queries
- Note AI Overview appearances
- Document organic vs. paid visibility
- Analyze competitor presence
2Phase 2: Build AI Foundation
- Create comprehensive, authoritative guides
- Contribute to Wikipedia
- Implement Schema.org structured data
- Build consistent NAP citations
- Secure editorial mentions in respected publications
3Phase 3: Maintain SEO Excellence
- Optimize Core Web Vitals
- Create content targeting featured snippets
- Build relationships with review sites
- Optimize shopping feeds
- Engage authentically on Reddit and forums
4Phase 4: Monitor and Adapt
- Monthly ChatGPT query testing
- Traditional rank tracking
- AI Overview appearance tracking
- Traffic source analysis
- Strategy refinement based on data
Conclusion: The Dual-Channel Future
The emergence of AI chatbots doesn't replace traditional SEO—it creates a dual-channel search landscape where success requires mastering both.
Key Takeaways
- ✅ Google and ChatGPT serve different needs - Gateway to web vs. self-contained answers
- ✅ Traffic models are fundamentally different - Google distributes, ChatGPT retains
- ✅ Source attribution matters - Google credits all sources, ChatGPT synthesizes
- ✅ Multiple visibility paths exist in Google - AI Overview + Organic + Paid + Shopping
- ✅ Brand control varies by query type - Comparisons allow owned content in Google
The Winning Strategy
Build the authoritative content that trains AI models while maintaining the SEO infrastructure that drives clicks, conversions, and customer journeys.
The question isn't "SEO or AI presence?"
It's "How do we excel at both?"
Ready to Boost Your AI Presence?
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