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AI SearchJanuary 15, 202615 min read

The Complete Guide to Generative Engine Optimization (GEO)

GEO is how you get cited by AI. Traditional SEO gets you ranked. GEO gets you into the answer.

HL

Hunter Lapeyre

Founder, Obieo & Lapeyre Roofing

AI Overviews appeared in 52% of tracked Google searches in early 2025 — up from just 6.49% in January. ChatGPT now commands over 4% of all search traffic, with 87% of AI referral traffic originating from OpenAI's chatbot.

The way people find information is changing. Traditional SEO optimizes for rankings. Generative Engine Optimization (GEO) optimizes for citations — being the source that AI pulls from when generating answers.

The Shift
By 2028, Gartner predicts a 50% reduction in traditional organic traffic due to AI-generated search. The businesses that adapt now will capture the traffic that others lose.

What is Generative Engine Optimization?

Generative Engine Optimization (GEO) is the practice of optimizing content to be cited, referenced, and surfaced by AI-powered search engines — ChatGPT, Perplexity, Google AI Overviews, Claude, and others.

Where traditional SEO asks "How do I rank #1?", GEO asks "How do I become the source the AI cites?"

Traditional SEO Goal

Rank #1

Appear at top of search results

GEO Goal

Get Cited

Be the source in AI answers

This isn't theoretical. I've seen it work firsthand. Six weeks after optimizing the Lapeyre Roofing website, I asked Google Gemini for Austin roofing recommendations. Lapeyre Roofing appeared alongside companies that have been in business for 40-50 years — Kidd Roofing (since 1982), Ja-Mar (50+ years), Wilson Roofing.

A newer company showing up alongside 50-year incumbents in AI recommendations. That's what GEO makes possible.

How AI Search Actually Works

To optimize for AI search, you need to understand how these systems select sources. Most AI search engines use a process called Retrieval-Augmented Generation (RAG).

The RAG Pipeline

1

Query Understanding

The AI interprets what you're asking — intent, entities, context. This is more sophisticated than keyword matching.
2

Retrieval

The system searches its index (web crawl, knowledge base, or real-time search) for relevant sources. This is where your content either gets pulled or ignored.
3

Ranking & Selection

Retrieved sources are ranked by relevance, authority, and recency. The top sources become candidates for citation.
4

Generation

The AI synthesizes information from selected sources into a response, citing the sources it drew from.
Critical Insight
Content under 3 months old is 3× more likely to be cited by AI systems. Freshness matters even more for GEO than traditional SEO.

Why Citation Selection Differs from Ranking

Traditional SEO rewards content that matches keywords and has strong backlinks. AI citation selection adds new factors:

  • Factual density — AI prefers content with specific claims, numbers, and verifiable facts
  • Structured information — Lists, tables, and clear hierarchies are easier to extract
  • Direct answers — Content that leads with the answer (not buries it) gets cited more
  • Source reputation — Community mentions (Reddit, forums) influence AI trust signals

Research shows that 95% of AI citation behavior is unexplained by traditional SEO metrics. The game has different rules.

The Citation Landscape

Different AI platforms have dramatically different citation patterns. Understanding where each AI pulls from is crucial for targeting your optimization.

ChatGPT Top Citations

47.9%

Wikipedia dominates

Perplexity Top Citations

46.7%

Reddit dominates

ChatGPT Citation Patterns

ChatGPT heavily favors Wikipedia, established news sources, and academic content. For local services, it leans on:

  • Wikipedia and established directories
  • News mentions and press coverage
  • Well-structured business websites with clear E-E-A-T signals

Perplexity Citation Patterns

Perplexity has a fundamentally different approach — it heavily indexes Reddit and community discussions. For local recommendations, it often pulls from:

  • Reddit threads (r/[city], r/HomeImprovement, etc.)
  • Nextdoor discussions
  • Forum recommendations and reviews
Strategic Implication
If your customers are using Perplexity, your Reddit and community reputation matters as much as your website. This is a completely different optimization target than traditional SEO.

Google AI Overviews

Google's AI Overviews primarily pull from content already ranking in the top 10. Research shows 76.1% of AI Overview citations also rank in Google's top 10, and 92.36% come from domains in the top 10.

This means traditional SEO and GEO are synergistic for Google — rank well, and you're more likely to be cited. But it also means the other 24% of citations come from sources that don't rank in the top 10, suggesting AI Overviews factor in different signals.

The llms.txt Protocol

llms.txt is an emerging standard that tells AI systems how to understand and interact with your website. Think of it as robots.txt for AI.

Current Adoption

0.3%

Of top 1,000 websites (June 2025)

Implementations

784+

Websites using llms.txt/llms-full.txt

What llms.txt Does

The file provides AI systems with:

  • Site purpose — What your site is about, who it serves
  • Key content — Which pages are most important for different queries
  • Entity information — Who you are, credentials, expertise areas
  • Preferred citation format — How you want to be referenced

Basic Implementation

Create a file at yoursite.com/llms.txt:

llms.txt
# Obieo
> SEO and GEO optimization for home service businesses

## About
Obieo helps contractors, roofers, and home service companies
dominate local search through SEO and AI search optimization.
Founded by Hunter Lapeyre, who also owns Lapeyre Roofing.

## Key Pages
- /: Homepage - overview of services
- /work/lapeyre-roofing: Case study with real results
- /blog: SEO and marketing insights for contractors
- /call: Book a strategy consultation

## Expertise
- Local SEO for home services
- Generative Engine Optimization (GEO)
- Contractor marketing strategy

## Contact
hunter@obieo.com
First-Mover Advantage
With only 0.3% of top sites implementing llms.txt, early adoption positions you as an AI-native brand. As AI search grows, this standard will likely become as important as robots.txt.

E-E-A-T for AI

Google's E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness) matters even more for AI citations than traditional rankings. AI systems are trained to favor authoritative sources.

Experience Signals

AI systems look for evidence of first-hand experience:

  • Case studies with specific results and timelines
  • First-person accounts ("When I implemented this...")
  • Original data from your own business
  • Photos, screenshots, documentation of real work

Expertise & Authority Signals

Structured data helps AI systems verify credentials:

  • Author schema — Link content to real people with verifiable expertise
  • Organization schema — Certifications, awards, affiliations
  • Review schema — Aggregated ratings and testimonials
  • LocalBusiness schema — Complete business information

Content with proper schema shows 30-40% higher visibility in AI-generated answers.

Trust Signals

AI systems cross-reference your claims against other sources:

  • Mentions in authoritative publications
  • Consistent information across web presence (NAP consistency)
  • Community discussions and organic mentions
  • Verified business listings (Google Business Profile, BBB, industry directories)

Agentic Commerce

The next frontier of AI search is agentic commerce — AI systems that don't just recommend, but actually complete transactions on behalf of users.

Projected Market

$3-5T

Agentic commerce by 2030

AI Conversion Rate

Higher than traditional search

Google's Universal Commerce Protocol (UCP)

Google is building infrastructure for AI agents to browse, compare, and purchase products. UCP standardizes how product information is structured so AI can:

  • Understand product specifications and pricing
  • Compare options across vendors
  • Complete purchases through standardized checkout

OpenAI's Checkout Integration

ChatGPT is integrating direct checkout capabilities. When users ask for product recommendations, ChatGPT can guide them through purchase without leaving the chat interface.

For Service Businesses
While direct checkout applies more to e-commerce, service businesses should prepare for AI-assisted booking. Structured service information, clear pricing, and easy scheduling integrations will become competitive advantages.

Measurement & Tools

Traditional analytics don't capture AI traffic well. Here's how to track your GEO performance:

AI Traffic Tracking

  • Referrer analysis — Track traffic from chat.openai.com, perplexity.ai, and Google AI referrers
  • Zero-click monitoring — Track impressions without clicks in Search Console
  • Brand mention tracking — Monitor when your brand appears in AI responses

Emerging Tools

The GEO measurement space is evolving rapidly:

  • Ahrefs Brand Radar — 100M+ prompt database for tracking AI mentions
  • SEMrush — Similar AI mention tracking with 100M+ prompts
  • Profound — Raised $35M Series B (Sequoia) for AI visibility analytics
  • AthenaHQ — Reports 10× AI traffic increases for customers

Implementation Roadmap

Start with the highest-impact, lowest-effort changes and build from there:

Phase 1: Foundation (Week 1-2)

1

Audit your current AI visibility

Search for your brand and services in ChatGPT, Perplexity, and Google AI Overviews. Document what appears — and what doesn't.

2

Implement llms.txt

Create a basic llms.txt file describing your business, key pages, and expertise areas.

3

Add structured data

Implement Organization, LocalBusiness, and Author schema. Use Google's Structured Data Testing Tool to validate.

Phase 2: Content Optimization (Week 3-4)

4

Lead with answers

Review your top pages. Move the direct answer to the first 150 words. No preamble, no "In this article we'll discuss..."

5

Add factual density

Include specific numbers, statistics, and verifiable claims. Cite sources. AI systems prefer content they can verify.

6

Structure for extraction

Use clear H2/H3 hierarchy, bulleted lists, comparison tables. Make it easy for AI to pull structured information.

Phase 3: Authority Building (Ongoing)

7

Build community presence

Engage authentically on Reddit, industry forums, and Nextdoor. These mentions influence AI recommendations, especially Perplexity.

8

Publish original research

Create content with unique data from your business. Case studies, benchmarks, and first-party insights are highly citable.

9

Monitor and iterate

Track AI mentions monthly. Adjust your strategy based on what's working and which platforms are driving results.

The Key Insight
47% of brands still lack a deliberate GEO strategy. Every month you wait, early adopters pull further ahead. The window for first-mover advantage is now.

GEO isn't replacing SEO — it's expanding it. The businesses that master both will dominate the next decade of search.

Related Reading

HL

Hunter Lapeyre

Hunter owns Obieo (SEO and GEO for home service businesses) and Lapeyre Roofing. He tests every strategy on his own business first — including the GEO tactics in this guide.

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