What Is GEO?

What Does GEO Mean?

GEO means Generative Engine Optimization: optimizing your content and broader digital presence to increase the likelihood that generative AI systems retrieve, understand, cite, mention, or recommend your information.

The term was introduced in a 2023 research paper titled GEO: Generative Engine Optimization by researchers from Princeton University, Georgia Tech, the Allen Institute for AI, and IIT Delhi. The researchers proposed GEO as a framework for helping content creators improve visibility within responses generated by generative engines.

That definition has since expanded in marketing.

Today, GEO generally includes efforts to improve visibility across AI-driven discovery experiences such as:

• ChatGPT
• Google AI Overviews
• Google AI Mode
• Perplexity
• Gemini
• Claude
• Microsoft Copilot
• Other AI-powered search and answer systems

The desired outcome isn’t always a clickable citation.

A brand might appear as:

• A cited source
• A linked recommendation
• A named product
• A company mention
• A summarized expert source
• Part of a comparison
• A factual reference
• An uncited brand recommendation

That’s why GEO ultimately connects to a broader concept: AI visibility.

If you’re unfamiliar with that measurement layer, Growth Gary’s guide to what AI visibility is explains it in more detail.

Why Does GEO Matter?

GEO matters because the way people find information is expanding beyond conventional search results.

Someone researching marketing software might still search Google for:

best CRM software for marketing

But they can also ask ChatGPT:

What are the best CRMs for a small marketing agency?

Or Perplexity:

Compare HubSpot, Pipedrive, and ActiveCampaign for a 10-person marketing team.

Or Gemini:

Which CRM is easiest to integrate with Google Workspace?

The user intent isn’t dramatically different.

The interface is.

Instead of reviewing several search results independently, the user may receive a synthesized response containing products, explanations, comparisons, recommendations, and sources.

That changes what visibility means.

A company can theoretically rank well in conventional Google results while being rarely mentioned in AI answers. Conversely, AI systems can surface sources and brands that don’t occupy the exact same traditional search positions.

Recent research comparing Google Search, AI Overviews, and Gemini found substantial differences between the sources retrieved by traditional and generative search experiences. The researchers also found variability between AI responses and even between slightly modified versions of the same query.

That’s important.

GEO isn’t simply “rank #1 in Google and you’ll automatically win AI search.”

There is overlap, but the systems aren’t identical.

How Does GEO Work?

GEO works by improving the signals and information AI systems may use when retrieving sources and constructing answers.

At a simplified level, an AI-powered search experience may:

1. Interpret the user’s question.
2. Determine whether external information is needed.
3. Search or retrieve potentially relevant information.
4. Evaluate and select sources.
5. Extract useful passages or facts.
6. Synthesize information into an answer.
7. Cite or link to some of the sources used.

Different platforms handle those steps differently.

Some AI systems rely heavily on live web retrieval. Others combine retrieval with information already represented in models or other systems. Search activation, source selection, reranking, citation behavior, and answer generation can all vary by platform and query. Recent GEO research argues that this complexity is precisely why GEO shouldn’t be treated as one simple ranking algorithm.

From a marketer’s perspective, the practical goal is much simpler:

Make your information easy to find, understand, trust, extract, and use.

If you want the deeper technical explanation of the retrieval and synthesis process, Growth Gary’s guide to how AI search works covers that separately.

What Is the Difference Between GEO and SEO?

GEO and SEO overlap significantly, but they optimize for different forms of visibility.

The mistake would be looking at that table and concluding that you now need to choose between SEO and GEO.

You don’t.

A lot of what helps GEO is simply good search and content strategy:

• Crawlable websites
• Strong topical relevance
• Helpful content
• Clear information architecture
• Credible sourcing
• Useful original information
• Strong brand authority
• Descriptive headings
• Accurate facts
• Third-party recognition

AI systems still need information to retrieve.

The web is a pretty good place to find it.

That’s why I think the more productive conversation is SEO + GEO, not SEO versus GEO. Growth Gary’s comparison of traditional SEO and AI search goes deeper into where the two approaches diverge.

GEO vs. AEO: What’s the Difference?

GEO and AEO are related terms with fuzzy boundaries.

AEO stands for Answer Engine Optimization. Traditionally, AEO focuses on structuring information so search and answer systems can provide concise answers to user questions.

That can include:

• Featured snippets
• Voice search
• Knowledge panels
• Direct answers
• FAQ-style responses
• AI-generated answers

GEO focuses specifically on generative systems that synthesize answers using AI.

A simple distinction is:

SEO → visibility in search results

AEO → visibility as an answer

GEO → visibility within generative AI answers

In practice, there’s substantial overlap.

Clear definitions, direct answers, structured information, useful examples, strong sourcing, and understandable content can support all three.

I wouldn’t spend too much energy debating whether one paragraph is “AEO optimized” or “GEO optimized.”

I’d spend that energy making the paragraph genuinely useful.

GEO vs. AI Visibility: What’s the Difference?

This distinction is more useful.

GEO is the optimization process. AI visibility is the outcome you’re trying to improve.

Think about traditional SEO:

SEO activity → search visibility

The AI equivalent is:

GEO activity → AI visibility

AI visibility can include how frequently a brand appears, where it appears, how prominently it appears, what prompts trigger the appearance, whether it’s cited, and how it’s characterized.

For example, suppose you monitor 100 relevant AI prompts.

Your company appears in:

• ChatGPT: 32 responses
• Perplexity: 41 responses
• Google AI: 27 responses
• Gemini: 18 responses

Those appearances are measurements of AI visibility.

The content, authority, technical, citation, and brand-building work you perform to improve those results is part of GEO.

What Does GEO Optimize?

GEO isn’t simply about optimizing a webpage.

That’s one of the biggest differences in how I think marketers should approach it.

Generative systems can draw information from a broader ecosystem of sources.

That means GEO can involve several layers.

Your Website

Your owned content remains important.

Useful GEO-oriented content tends to provide clear information that can stand on its own when extracted from the surrounding page.

That can include:

• Definitions
• Direct answers
• Statistics
• Comparisons
• Step-by-step processes
• Examples
• Tables
• Expert explanations
• Original research
• Product information
• FAQs where genuinely useful

The objective isn’t to write like a robot because you’re hoping another robot likes it.

It’s to remove ambiguity.

Your Brand and Entities

AI systems need to understand who and what you’re talking about.

Clear entity information can help establish relationships between:

• Companies
• Products
• People
• Services
• Categories
• Locations
• Topics

If your website describes your company five different ways, third-party websites describe it another three ways, and nobody can clearly determine what you actually do, that’s not ideal for humans or machines.

Consistency helps.

Third-Party Sources

This is where GEO expands beyond on-page optimization.

AI systems may use information from:

• News publications
• Industry websites
• Review sites
• Forums
• Reddit
• YouTube
• Academic sources
• Professional organizations
• Product directories
• Comparison websites
• Other authoritative publishers

You don’t control those sources.

But they can influence how your brand is represented across the information ecosystem.

This is one reason digital PR, thought leadership, reviews, citations, partnerships, and genuine industry recognition can become relevant to GEO.

Technical Accessibility

A brilliant resource isn’t very useful to a retrieval system if the system can’t access it.

Technical considerations can include:

• Crawlability
• Indexability
• Internal linking
• Site architecture
• Page performance
• Renderability
• Structured data
• Canonicalization
• Robots directives

This is where traditional technical SEO remains foundational.

GEO didn’t suddenly make technical SEO obsolete.

If anything, adding more discovery systems makes clean technical foundations more useful.

What Makes Content Good for GEO?

There isn’t a universal “GEO formula.”

Anyone promising one should make you slightly nervous.

Generative engines differ, change frequently, and don’t expose a single ranking algorithm marketers can reverse engineer.

Research published in 2026 also cautions against assuming that isolated GEO tactics produce stable, cross-platform gains. The evidence is still developing, and performance can vary significantly by platform, query, domain, and retrieval context.

That said, several principles make sense because they improve the underlying information.

Answer Questions Directly

If the heading asks:

What is generative engine optimization?

Don’t spend four paragraphs warming up.

Answer it.

Generative engine optimization is the practice of improving content and digital presence to increase visibility in AI-generated answers.

Then explain.

Clear answers help readers and make individual passages easier for retrieval systems to interpret.

Create Self-Contained Sections

AI systems may retrieve a passage rather than evaluate your article exactly as a human reads it from beginning to end.

That makes context important.

Compare:

Weak:

This is why it matters so much.

With:

Better:

GEO matters because AI search systems can answer questions directly, reducing the user’s need to visit traditional search results.

The second sentence survives extraction.

The first doesn’t.

Support Claims With Evidence

Specific, attributable information is more useful than vague claims.

That can include:

• Original research
• Industry studies
• Government data
• Academic research
• First-party datasets
• Expert sources
• Clearly attributed statistics

Don’t add random statistics just because someone told you “AI loves numbers.”

Use evidence when evidence improves the answer.

Make Comparisons Explicit

AI users frequently ask comparative questions:

• X vs. Y
• Best tool for X
• Difference between X and Y
• Advantages of X
• Alternatives to X

Clear comparison tables and structured explanations make those relationships easier to understand.

Demonstrate Real Expertise

Generic content is easy to produce.

Actual expertise is harder.

Useful differentiators include:

• Original research
• Firsthand experience
• Expert commentary
• Proprietary data
• Unique examples
• Detailed methodology
• Specific analysis

AI can generate another generic definition of SEO in about five seconds.

The web doesn’t desperately need the 40 millionth version.

Give the information ecosystem something worth retrieving.

Do Keywords Matter for GEO?

Yes—but not in exactly the same way they matter in conventional keyword-driven SEO.

People interacting with AI systems often use longer, conversational prompts.

Instead of:

CRM software

they might ask:

What’s the best CRM for a five-person marketing agency that uses Gmail and doesn’t need enterprise sales features?

That’s a much richer expression of intent.

For GEO, marketers should think beyond individual keywords toward:

• Topics
• Questions
• Entities
• Problems
• Use cases
• Comparisons
• Attributes
• Buying criteria
• Follow-up questions

Keywords are still useful because they reveal demand and language.

They just aren’t the entire map.

What Are AI Citations and Why Do They Matter for GEO?

An AI citation is a source reference used or displayed alongside an AI-generated response.

Citations can help users understand where information came from and provide a path to the original source.

For marketers, citations are particularly valuable because they create measurable evidence that content is being surfaced by an AI system.

But citation isn’t the only form of visibility.

Imagine an AI answer says:

Popular options include HubSpot, Salesforce, and Pipedrive.

Pipedrive received a valuable brand mention even if the response didn’t cite Pipedrive’s website.

That’s why GEO measurement should include both:

Citations + mentions

Recent research has gone even further, distinguishing between whether a source gets selected for citation and how much its information actually influences or is “absorbed” into the generated answer.

Growth Gary’s guide to what AI citations are covers that specific part of AI visibility in more detail.

How Do You Measure GEO?

GEO measurement is still developing.

There isn’t one equivalent of “Google position #3” that tells the entire story.

Useful metrics can include:

Measurement also needs repetition.

Generative answers aren’t necessarily deterministic.

Ask the same system the same question multiple times and you may get different sources, recommendations, wording, or ordering. Research into AI Overviews and Gemini has documented this variability as well.

So don’t celebrate because ChatGPT mentioned your company once on Tuesday afternoon.

Track patterns.

Can GEO Guarantee AI Citations?

No.

Nobody can guarantee that ChatGPT, Google AI Overviews, Perplexity, Gemini, or another generative system will cite your content.

There are too many variables:

• The user’s prompt
• Search activation
• Retrieval systems
• Available sources
• Model behavior
• Platform changes
• Competitors
• Personalization
• Location
• Freshness
• Query interpretation

GEO should improve the conditions that make visibility possible.

It doesn’t give marketers control over the final answer.

That’s an important distinction because this industry is currently experiencing the predictable phase where every new marketing discipline acquires a small army of people selling certainty.

Be skeptical of certainty.

What Are Common GEO Mistakes?

GEO is new enough that marketers are already finding creative ways to overcomplicate it.

Treating GEO as a Replacement for SEO

This is probably the biggest mistake.

If your website has poor architecture, weak content, no authority, indexing problems, and little relevance to the topic, adding “GEO optimization” isn’t going to magically fix the foundation.

Start with good search fundamentals.

Writing for AI Instead of People

Don’t turn every paragraph into a sterile 47-word answer block because someone told you ChatGPT likes “chunks.”

Clear structure is useful.

Awkward writing isn’t.

Your primary audience is still human.

Creating Generic AI Content at Scale

Producing 10,000 mediocre pages with AI isn’t automatically a GEO strategy.

If every competitor can produce essentially the same information, you’ve created very little reason for your version to become a preferred source.

Focusing Only on Your Website

Your owned website matters, but your broader presence matters too.

Brand mentions, reviews, discussions, expert contributions, third-party articles, videos, community conversations, and other sources can all contribute to the information AI systems encounter.

Obsessing Over Unproven Technical Hacks

You’ll hear about special files, magic schemas, prompt injection tricks, AI-specific metadata, and various methods supposedly guaranteed to unlock LLM visibility.

Be careful.

Some technical practices may become useful as the ecosystem develops. Others may turn out to have little practical impact.

Don’t prioritize speculative tricks over content quality, accessibility, authority, and actual brand recognition.

Trying to Manipulate Recommendations

GEO shouldn’t mean flooding the web with fake recommendations designed to convince AI systems your product is the “best.”

Besides being terrible marketing, manipulative tactics aimed at altering generative search results can run directly into platform spam policies. Google, for example, has expanded its spam framework to explicitly address attempts to manipulate generative AI features.

Build real evidence.

It’s slower.

It’s also considerably harder for competitors to fake.

How Do You Start With GEO?

If you’re starting from scratch, don’t rebuild your entire marketing strategy around AI search.

Start with a focused process.

1. Identify Important Topics

Determine the questions and buying decisions where visibility matters to your business.

Don’t track random prompts just because a tool gives you a big dashboard.

Track commercially and strategically meaningful questions.

2. Establish Your Current AI Visibility

Test how your brand appears across relevant AI platforms.

Look for:

• Mentions
• Citations
• Competitors
• Source domains
• Missing topics
• Incorrect information

This gives you a baseline.

3. Analyze Which Sources AI Systems Use

If competitors consistently appear and you don’t, investigate why.

Which websites are being cited?

What information do those pages contain?

Are third-party sources repeatedly recommending certain brands?

This is often more useful than staring exclusively at your own site.

4. Improve Your Existing Content

Before publishing 200 new pages, improve important existing ones.

Make sure they provide:

• Direct answers
• Clear definitions
• Useful comparisons
• Credible evidence
• Logical headings
• Strong topical coverage
• Accurate information

5. Strengthen Your Broader Brand Presence

Look beyond your domain.

Identify the publications, communities, directories, review platforms, experts, and other sources that matter within your market.

The goal isn’t to manufacture mentions.

It’s to become worth mentioning.

6. Measure Again

Repeat the original prompt set.

Compare:

Before → after

Then keep doing what appears to work and stop doing what doesn’t.

That’s marketing.

The acronym is new. The discipline isn’t.