Rank in AI Search: ChatGPT & Google AI Overviews Strategy

TL;DR: Do This To Rank in AI

  • Be active on Reddit (1/3 of AI citations come from there)
  • Build review velocity across platforms (AI systems prioritize trust signals and momentum)
  • Structure content with direct answers first (40–60 word summaries)
  • Optimize for Bing (ChatGPT’s search source)
  • Use schema markup (FAQ/HowTo schemas get pulled 11x more)
  • Create ultra-specific content (niche beats generic in AI)
  • Track AI visibility with tools (Ahrefs Brand Radar, xfunnel, Waikay)
  • Think beyond SEO (optimize for AEO – Answer Engine Optimization)

Search has fundamentally changed. We’ve evolved from the early pre-Google era of shoddy search results (hello, Lycos and AltaVista!), through the familiar “10 blue links,” to today’s “inference search” where AI systems synthesize information from multiple sources to provide direct answers. This represents the shift from answer engines to action engines. Users now complete their entire buyer’s journey within AI, moving from problem to solution almost instantly. This emerging space is known as Answer Engine Optimization (AEO), a strategic approach to gaining visibility in AI-generated answers, not just traditional search rankings. As this field evolves, a more specific discipline has emerged: Generative Engine Optimization (GEO), which focuses on optimizing for the generative AI models themselves, ensuring your brand and content are a part of the AI’s answer.

At Funk/Levis, we’ve achieved strong AI overview representation through extensive research and testing. Here’s our current playbook for getting visibility in this new landscape.

The New Search Reality

AI-powered search has disrupted traditional SEO faster than anyone predicted. ChatGPT’s nearing 1 billion users (which took Google nearly 13 years), and users are increasingly saying “I’ll ChatGPT” instead of Google for their queries. ChatGPT’s adoption speed signals a fundamental shift in user behavior.

The stakes are transformational. Industry data from sources like SEMrush shows LLM visitors are worth 4.4x more than traditional search traffic because they complete their buyer’s journey within the AI interface. By the time they click through to your site, the nurturing has already happened. They’re often ready to buy or talk to sales. When Google AI Overviews appear for a search result, the number one organic result gets around 35% less traffic.

Yet this isn’t entirely negative. 

The new metric: Share of voice in AI responses matters more than raw visits. You’re no longer optimizing for clicks; you’re optimizing for citations and brand mentions in AI-generated answers. This is the core of GEO. Track your AI share of voice using SEMrush‘s AI Overview tracker or Ahrefs‘ ‘Cited Domains’ report to monitor citation frequency for target queries. Xfunnel lets you segment AI citations by persona or customer journey stage so you can pinpoint whether you’re being recommended during early research, evaluation or buying moments.

New reporting visibility: As of June 2025, Google Search Console now includes data from AI Mode meaning impressions, clicks and positions for AI-generated responses are counted in your performance reports. While you still can’t isolate AI Mode traffic, this inclusion means your AI visibility now contributes to total reported search performance.

Importantly, follow-up questions in AI Mode are counted as new searches (so even deeper interactions with your content are measurable as separate impressions and clicks).

Why AI Systems Favor User-Generated Content

AI models are actively seeking signals of first-hand human experience to add authenticity and depth to their answers. This is the “Experience” in E-E-A-T in action. That’s why Reddit accounts for 32% of Google AI Overview citations and Quora frequently appears as well. These platforms provide the genuine insights that AI systems need to ground their responses in real-world experience. Your ability to build these signals is a key component of GEO.

Users now research and compare options within AI interfaces, arriving at your site pre-qualified and ready to act.

Related Resource: Website Power Checklist

Turn your site from passive to powerful with our checklist to drive conversions from AI-fueled traffic.

Download Now

Core Strategies for AI Visibility

1. Build Verifiable Authority Through E-E-A-T

Experience, Expertise, Authoritativeness and Trustworthiness have evolved from conceptual guidelines to machine-readable signals that define AI inclusion. 

Experience signals:

  • Include genuine user reviews and testimonials directly on pages
  • Publish detailed case studies with verifiable data and outcomes
  • Write from first-person perspective where appropriate (“In our testing…”)
  • Add original photography/videos showing products in actual use

Authority and trust signals:

  • Create comprehensive author bios with credentials, link to social/professional profiles and use Person and author schema markup. Alternatively, showcase team credentials on ‘About Us’ pages with Person schema, cite client results with verifiable data (‘Law firm X saved 20 hrs/week using our CRM’) and use Organization schema for company awards and expertise when individual authorship isn’t feasible.
  • Cite authoritative primary sources for all factual claims
  • Maintain accurate presence in Google’s Knowledge Graph by claiming your Knowledge Panel and using robust Organization schema markup
  • Ensure transparent contact information and robust “About Us” pages

Your current business reviews serve as powerful trust markers. These act as external validation of your Authority and real-world Experience. Research shows:

  • Review velocity matters more than perfect ratings. Research across 15,000 business locations shows that businesses pulling in 3-5 reviews per day consistently outrank competitors with higher star ratings but slower review velocity. The key insight: AI systems prioritize ongoing signals of relevance and engagement over static ratings.
  • 92% of consumers now see responding to reviews as basic customer service, not bonus behavior. This creates a revenue opportunity – businesses that respond to reviews signal accessibility and care, directly influencing buying decisions.
  • Timing is everything for review requests. Ask at the moment of service, then follow up within 24 hours using email or SMS. Train frontline staff to make in-person requests backed by physical signage and QR codes at point of service.

2. Master Key Information Platforms

Reddit dominance: Reddit’s 32% share of Google AI Overview citations makes authentic participation non-negotiable. Focus on providing genuine insights, not promotional content.

Reddit and community strategy:

  • Identify 2-3 active subreddits where your target audience discusses problems you solve
  • Provide 3-5 substantive answers weekly in target subreddits. Focus on depth: 100+ words with actionable advice or data snippets (e.g., ‘In our case studies, X workflow saved 40% time’)
  • Answer questions and establish expertise organically before sharing your content
  • Build brand mentions through helpful contributions to conversations
  • Set up alerts with GummySearch or use BrandMentions to track where your brand shows up in Reddit conversations. For broader brand integrity across AI platforms, tools like Waikay help flag incorrect information AI models might be citing about your brand.

The data confirms brand mentions count as algorithmic votes across the web, not just on Reddit. AI systems treat these mentions as credibility signals that train models to associate your brand with relevant terms and use cases, whether those mentions include backlinks or not.

Diversify your review strategy beyond Google. Since 60% of AI Overview citations come from third-party platforms like Yelp, TripAdvisor, and industry-specific sites, relying solely on Google reviews leaves your moat unprotected. Use dynamic links or conditional logic to rotate review requests across platforms – except Yelp, which prohibits solicited reviews.

3. Structure Content for AI Consumption

Structure content for easy AI parsing.

The answer-first approach:

  • Start articles with direct, concise answers to the main question (40-60 words)
  • Use clear headings (H2s, H3s) that mirror question structures
  • Break down complex topics with bullet points and numbered lists
  • Write in simple, unambiguous language that AI can easily extract and quote

Make content scannable:

  • Use the inverted pyramid structure: key information first, details follow
  • Keep paragraphs short (2-4 sentences) and focused on single concepts
  • Include FAQ sections that directly address common user questions
  • Optimize each section to stand alone and clearly address a query (AI often selects 40-70 word spans)

Target conversational queries: Instead of “CRM software,” they ask “What’s the best CRM for a small law firm that needs client communication tracking?” Even basic internal surveys (‘What’s your biggest CRM pain?’) or aggregated support tickets can become compelling ‘State of X’ blog posts that LLMs love to cite.

Schema markup specifics: Use tools like Google’s Rich Results Test or plugins like RankMath/Yoast to add FAQ and HowTo schema. Prioritize HowTo schema for tutorials (11x more likely to be pulled into step-by-step answers) and FAQ for definitions.

Short on dev resources? Prioritize HowTo and FAQ schemas as they’re most likely to be pulled into AI summaries and easiest to implement via plugins.

4. Leverage Original Data as Your Differentiator

AI systems prioritize unique, first-hand information that can’t be found elsewhere. Your customer data becomes your competitive moat.

Data-driven content strategy:

  • Include proprietary insights from your customer base (anonymize client data in bulk)
  • Publish original research, even if small-scale. Leverage AI to do the heavy data analysis lifting
  • Use specific metrics from your experience (“manufacturing companies see 3x higher close rates”)
  • Create content that demonstrates why your solution works for specific scenarios

5. Technical Excellence Remains Non-Negotiable

Websites that will appear most in AI Overviews will load under 2.5 seconds. AI systems favor content that’s easily accessible and parseable.

Technical requirements:

  • Ensure fast page speeds and mobile optimization. Get pagespeed insights
  • Implement comprehensive schema markup: FAQ, HowTo, Article, Organization and Product schemas
  • Check your robots.txt file for Disallow rules that might be blocking GPTBot or ChatGPT-User
  • Use structured data to explicitly communicate content meaning to machines

ChatGPT-Specific Optimization

ChatGPT uses Bing’s search API for real-time information:

Bing SEO focus:

  • Verify your site in Bing Webmaster Tools and submit updated sitemaps
  • Build quality backlinks recognized by Bing
  • Target long-tail keywords with 15+ words (Bing’s algorithm favors specificity)

Pro Tip: Use Bing Webmaster Tools‘ ‘Inbound Links’ report to spot which content Bing considers authoritative – then double down on that format.

47.9% of ChatGPT’s citations come from Wikipedia (SEORoundTable). For established brands, ensuring factually accurate and well-maintained Wikipedia presence is one of the most direct ways to influence ChatGPT responses.

Try to write the most specific and credible answer to a niche question. ChatGPT often cites these over traditionally authoritative domains, creating opportunities for newer, focused content.

Content Strategy Revolution

Build content targeting ultra-specific scenarios rather than generic guides. Each page should address a particular persona with specific context and constraints. Generate 50+ variants from one pillar piece using this prompt: ‘Expand [Topic] into scenarios targeting [Persona] struggling with [Constraint]. Output as H2-driven sections with 60-word summaries.’

Move beyond “how to do X” content toward “why we’re the best solution for X given Y constraints.” When an LLM formulates answers, it pulls from content that clearly explains why specific products or services solve particular problems.

Links still drive the lion’s share of topical authority for AI inclusion, while mentions train LLMs on your expertise. Focus on both rather than choosing one over the other.

Looking Ahead: The Open Field Advantage

This transition represents the biggest opportunity in marketing since the early days of SEO. The rules are being rewritten, creating an open field where new entrants can gain visibility in days rather than months.

Strategic advantages for early adopters:

  • No one has a significant edge yet. Success goes to those who figure out new tactics quickly
  • AI-powered content systems level the playing field (you don’t need huge teams)
  • Specificity beats authority in many AI citation decisions for niche queries
  • Fresh, targeted content can outperform established but generic pages

Good AI SEO practices often help traditional Google rankings too. This isn’t a zero-sum game between old and new search.

The companies that adapt early while maintaining strong traditional SEO foundations will dominate visibility in the AI-powered search landscape that’s already here.

Want To Level Up Your Marketing?

Get free access to our library of proven tools & strategies to grow your brand. Plus, stay ahead of the curve with expert tips—sign up for our Strategic Spark Newsletter today!

Explore Our Resources
Sign Up Now!