SEO vs AEO vs GEO vs LLMO: What's the Difference?

Understanding the Four Pillars of Modern Search Optimization

Modern search optimization isn't one discipline anymore—it's four interconnected approaches working together.

SEO (Search Engine Optimization) focuses on ranking in traditional search results through technical excellence, content relevance, and authority building.

AEO (Answer Engine Optimization) targets direct-answer formats like featured snippets, voice search results, and knowledge panels.

GEO (Generative Engine Optimization) specifically addresses AI-generated search results like Google AI Overviews.

LLMO (Large Language Model Optimization) ensures your brand appears accurately and prominently when AI assistants like ChatGPT, Claude, and Perplexity generate responses.

These aren't competing strategies. They're complementary layers of a unified approach to search visibility in 2026 and beyond. The businesses winning today are those integrating all four.

Key Takeaways

Learn how SEO, AEO, GEO, and LLMO work together to build visibility across traditional search and AI platforms.

1. Modern search optimization is four disciplines, not one.
SEO builds rankings, AEO wins direct answers, GEO targets AI Overviews, and LLMO ensures visibility in AI assistants. Each has distinct requirements but all work together.
2. SEO remains the foundation.
Authority signals from traditional SEO feed directly into AI systems. Without strong organic foundations, AI optimization efforts lack the credibility base they need to succeed.
3. AEO bridges traditional and AI search.
Content structured for featured snippets and voice search translates directly to AI extractability. Mastering AEO prepares your content for AI consumption.
4. GEO and LLMO address different AI contexts.
GEO optimizes for Google AI Overviews within search results. LLMO ensures visibility when users query AI assistants directly, bypassing search entirely.
5. Integration beats isolation.
The most effective strategy treats all four as layers of a unified approach—each building on the others rather than competing for attention.

Why the Landscape Has Fragmented

Ten years ago, search optimization meant one thing: ranking in Google. You optimized for keywords, built backlinks, improved site speed, and watched your rankings climb.

That singular focus no longer captures the full picture of how people find information online.

Users now get answers from multiple sources and formats. They might see a featured snippet before the first organic result. They might ask their voice assistant instead of typing. They might skip Google entirely and ask ChatGPT. They might scan Google's AI Overview and never scroll to the traditional results.

Each of these pathways has different requirements for visibility. A page that ranks #1 organically might not appear in the AI Overview. Content optimized for featured snippets might not be what ChatGPT cites. Voice search optimization requires different structural considerations than text-based search.

This fragmentation isn't a problem to solve—it's a reality to navigate. And navigating it requires understanding each optimization discipline on its own terms, then integrating them strategically.

SEO: The Foundation That Still Matters

Search Engine Optimization remains the bedrock of search visibility. Despite all the changes in how people find information, traditional organic rankings haven't disappeared—and the signals that drive them feed directly into newer AI systems.

What SEO Focuses On

Technical Infrastructure Site speed, mobile responsiveness, crawlability, indexation, secure connections (HTTPS), and structured data implementation. These technical foundations ensure search engines can access, understand, and evaluate your content.

Content Relevance Creating content that matches user intent for target queries. This involves keyword research, topical coverage, content depth, and alignment between what users search for and what your pages deliver.

Authority Building Earning backlinks from credible sources, building brand recognition, and establishing your site as a trusted resource in your field. Authority signals tell search engines your content deserves to rank.

User Experience Engagement metrics, clear navigation, intuitive design, and content that satisfies user needs. Search engines increasingly factor user behavior into ranking decisions.

Why SEO Still Matters for AI Search

Every AI search platform uses authority signals when deciding what to cite. Google AI Overviews heavily favor pages that already rank well organically. ChatGPT and Perplexity evaluate source credibility using many of the same signals traditional SEO builds.

Strong SEO creates the authority foundation that makes AI citation more likely. Neglecting SEO fundamentals undermines everything else you might do for AI visibility.

The Limitations of SEO Alone

Traditional SEO gets you onto the results page. But in an AI-mediated search landscape, appearing on the page isn't the same as being cited in the answer.

A page ranking #3 organically might be completely absent from the AI Overview at the top of the results. A site with strong backlinks might never be mentioned when someone asks ChatGPT for recommendations.

SEO is necessary but no longer sufficient. It must be supplemented with optimization approaches designed for how AI systems consume and cite content.

AEO: Optimizing for Direct Answers

Answer Engine Optimization emerged as search engines began providing direct answers rather than just links. Featured snippets, knowledge panels, "People Also Ask" boxes, and voice search results all represent answer-first formats where a single source gets prominent, above-the-fold visibility.

What AEO Focuses On

Question-Based Content Structure Organizing content around specific questions your audience asks. Clear questions followed by direct, concise answers make it easy for answer engines to extract and display your content.

Featured Snippet Optimization Formatting content specifically for the featured snippet formats Google uses: paragraphs, lists, tables, and step-by-step instructions. Each format has structural requirements that increase selection likelihood.

Voice Search Optimization Creating content optimized for how people speak rather than type. Voice queries tend to be longer, more conversational, and often location-specific. Content that matches these patterns performs better in voice results.

Concise, Authoritative Answers Providing clear, direct answers that can stand alone when extracted from surrounding context. Answer engines need content that makes sense as a standalone response.

How AEO Differs from Traditional SEO

Traditional SEO optimizes for ranking among a list of results. AEO optimizes for being the single answer selected for prominent display.

This distinction matters because answer selection involves different criteria than ranking. A page might rank well without ever being selected for a featured snippet. Conversely, a page might capture featured snippets while ranking lower in traditional results.

AEO requires thinking about content as a source of extractable answers, not just a destination for clicks.
The Relationship Between AEO and AI Search

AEO principles translate directly to AI search optimization. The same content structures that win featured snippets—clear questions, direct answers, logical organization—make content more extractable for AI citation.

AEO can be understood as the bridge between traditional SEO and the AI-specific optimizations of GEO and LLMO. Mastering AEO principles prepares your content for AI consumption.

GEO: Optimizing for Google's AI Overviews

Generative Engine Optimization addresses the specific requirements of AI-generated search results—most notably Google's AI Overviews, which now appear atop results for a significant and growing percentage of queries.

What GEO Focuses On

AI Overview Targeting Identifying which queries trigger AI Overviews and prioritizing content optimization for those queries. Not every search generates an overview; strategic focus matters.

Multi-Source Synthesis Awareness Understanding that AI Overviews synthesize information from multiple sources. Your content needs to contribute valuable, citable elements even when it won't be the only source referenced.

Extractable Statement Density Creating content with high concentrations of clear, specific, quotable statements. Each discrete fact or insight is a potential citation opportunity.

Traditional Authority Maintenance Maintaining strong organic rankings, since AI Overviews heavily favor authoritative sources. GEO doesn't replace SEO—it builds on top of SEO foundations.

How AI Overviews Select Sources

Google's AI Overviews don't simply copy content from top-ranking pages. They evaluate sources based on relevance to the specific query, clarity and extractability of information, authority and trustworthiness, and how well the content contributes to a comprehensive answer.

A page might rank #1 but not be cited in the overview if its content is poorly structured for extraction. Conversely, a page ranking lower might be cited if it provides the clearest, most directly relevant answer to a specific aspect of the query.

GEO-Specific Tactics

Format Diversification AI Overviews pull from text, lists, tables, and structured data. Creating content in multiple formats increases citation opportunities.

Comprehensive Coverage Pages that thoroughly address a topic from multiple angles provide more potential citation points than thin content.

Clear Attribution Signals Author credentials, publication dates, and source indicators help AI Overviews evaluate and cite your content confidently.

Regular Updates AI Overviews favor current information. Maintaining and updating content signals ongoing relevance.

LLMO: Optimizing for AI Assistants

Large Language Model Optimization is the newest frontier—ensuring your brand appears accurately and prominently when users query AI assistants like ChatGPT, Claude, Perplexity, and Microsoft Copilot directly.

What LLMO Focuses On

Training Data Presence Understanding that LLMs learn from vast text datasets. Consistent brand presence across authoritative sources increases the likelihood of accurate representation in AI training.

Retrieval System Optimization Many AI assistants now use real-time web retrieval (RAG—Retrieval Augmented Generation) to supplement their training data. Content optimized for retrieval gets cited in current responses.

Brand Entity Consistency Ensuring consistent information about your business across all platforms AI systems might reference. Inconsistency creates confusion; consistency builds citation confidence.

Expertise Signal Amplification Making credentials, experience, and authority unmistakably clear. AI assistants evaluate source quality when deciding what to cite.

How LLMO Differs from GEO GEO focuses specifically on Google's AI Overviews within the search results page. LLMO addresses AI assistants as standalone platforms—environments where users might never see a traditional search result at all.

Someone asking ChatGPT "What marketing agency should I use in Kansas City?" isn't seeing search results. They're seeing whatever ChatGPT generates. LLMO ensures your brand can be part of that response.

The Unique Challenges of LLMO

Training Data Lag LLMs are trained on historical data. Information about your business from years ago might be what the model "knows." Ongoing authoritative presence helps ensure current information eventually reaches training datasets.

Black Box Evaluation Unlike Google, which provides Search Console data, AI assistants offer limited visibility into how they evaluate sources. LLMO requires inference and testing rather than direct measurement.

Platform Fragmentation Each AI assistant has different training data, retrieval approaches, and citation behaviors. What works for ChatGPT might not work identically for Claude or Perplexity.

LLMO-Specific Tactics

Multi-Platform Authority Building Establish presence on platforms AI systems reference: Wikipedia (if notable), industry publications, major news sites, professional directories, and high-authority websites in your sector.

Consistent Entity Information Ensure your business name, description, key personnel, services, and differentiators are consistent everywhere they appear online.

Structured Data Excellence Comprehensive schema markup helps AI retrieval systems understand your content contextually.

Original Research and Proprietary Insights Content that can only be attributed to you—original studies, unique methodologies, proprietary data—creates compelling citation opportunities.

How the Four Approaches Work Together

These disciplines aren't separate silos. They're interconnected layers that reinforce each other when implemented strategically.

SEO Feeds Everything Else

The authority you build through traditional SEO directly impacts your performance across AEO, GEO, and LLMO. Backlinks, domain authority, and brand recognition are evaluated by every system.
Without SEO foundations, the other optimizations lack the authority base they need to succeed.

AEO Principles Enable AI Extraction

The content structures that win featured snippets—clear questions, direct answers, logical organization—are exactly what AI systems need to extract and cite information.

Mastering AEO creates content that AI platforms can work with.

GEO and LLMO Share Core Requirements

Both GEO and LLMO require content optimized for AI extraction, strong expertise signals, consistent entity information, and regular content maintenance.

The tactics overlap significantly. Content optimized for Google AI Overviews is likely to perform well when cited by ChatGPT, and vice versa.

The Integrated Strategy

The most effective approach treats these four disciplines as facets of a single strategy:

Foundation Layer: SEO Technical excellence, content relevance, authority building, and user experience optimization.

Extraction Layer: AEO Content structured for direct-answer formats, question-based organization, and concise authoritative responses.

Google AI Layer: GEO AI Overview targeting, extractable statement density, format diversification, and traditional authority maintenance.

AI Assistant Layer: LLMO Multi-platform presence, entity consistency, retrieval optimization, and original insight development.

Each layer builds on the ones beneath it. Skipping layers undermines the whole structure.

Common Questions About the Four Approaches

Which should I prioritize?

Start with SEO if your foundations are weak—nothing else works without authority. If your SEO is solid, focus on AEO and GEO together, since they share many requirements. Add LLMO-specific tactics as resources allow.

Do I need separate content for each?

No. Well-structured, authoritative content can serve all four purposes. The key is ensuring your content meets the requirements of each approach: technically sound, answer-formatted, extractable, and consistently attributed.

How do I measure success across all four?

SEO and AEO have established measurement approaches through Google Search Console and rank tracking. GEO measurement is emerging through AI Overview tracking tools. LLMO requires manual testing—querying AI assistants and documenting how your brand appears.

Is this just for large businesses?

No. Small businesses with genuine expertise in specific areas can outperform larger competitors across all four dimensions. AI systems reward depth and authenticity over size and budget.

Building Your Unified Strategy

Understanding these four approaches conceptually is the first step. Implementing them requires a systematic approach:

Audit your current state. Assess your performance across traditional rankings, featured snippets, AI Overviews, and AI assistant responses.
Strengthen foundations first. Ensure your technical SEO, content quality, and authority signals are solid before layering on AI-specific optimizations.
Structure content for extraction. Reorganize existing content and create new content with clear, quotable statements and logical information hierarchies.
Build consistent entity presence. Ensure your business information is accurate and consistent across every platform AI systems might reference.
Measure and iterate. Track performance across all four dimensions and refine your approach based on what's working.

This guide is part of dameSpeak's AI Search Optimization resource library. For personalized guidance on integrating SEO, AEO, GEO, and LLMO for your business, contact our team.

Frequently Asked Questions

1. What does SEO stand for and what does it focus on? SEO stands for Search Engine Optimization. It focuses on improving your website's visibility in traditional search engine results through technical infrastructure, content relevance, authority building via backlinks, and user experience optimization. SEO remains foundational because the authority signals it builds feed directly into how AI systems evaluate source credibility.

2. What is AEO and how is it different from SEO? AEO stands for Answer Engine Optimization. While SEO focuses on ranking among a list of results, AEO focuses on being selected as the single answer for direct-answer formats like featured snippets, knowledge panels, and voice search results. AEO requires content structured around specific questions with clear, extractable answers that can stand alone when displayed prominently above traditional results.

3. What does GEO mean in search optimization? GEO stands for Generative Engine Optimization. It specifically addresses AI-generated search results like Google AI Overviews—the AI summaries that appear at the top of search results for many queries. GEO combines traditional SEO authority signals with content structured for AI extraction, format diversification, and extractable statement density.

4. What is LLMO and why does it matter? LLMO stands for Large Language Model Optimization. It ensures your brand appears accurately when users query AI assistants like ChatGPT, Claude, and Perplexity directly—environments where traditional search results may never appear. LLMO focuses on training data presence, retrieval system optimization, consistent entity information, and expertise signal amplification.

5. Do I need separate strategies for SEO, AEO, GEO, and LLMO? No. These approaches work best as integrated layers of a single strategy rather than separate initiatives. Well-structured, authoritative content can serve all four purposes. The key is ensuring your content meets each approach's requirements: technically sound for SEO, answer-formatted for AEO, extractable for GEO, and consistently attributed for LLMO.

6. Which optimization approach should I prioritize first? Start with SEO if your foundations are weak—nothing else works without authority. If your SEO is solid, focus on AEO and GEO together since they share many requirements. Add LLMO-specific tactics as resources allow. The goal is building layers progressively rather than choosing one approach over others.