What Is Generative Engine Optimization (GEO)? Understanding the New Search Landscape

When someone asks an AI assistant a question, it doesn't return ten links. It generates an answer, often drawing on several sources and sometimes citing them. Generative engine optimization (GEO) is the emerging practice of helping your content, and your organization, be accurately represented in those generated answers.

This article explains where the term comes from, what is actually known, and what practical GEO looks like. For how it compares with AEO and SEO, see AEO vs GEO vs SEO.

Where the term comes from

"Generative engine optimization" was popularized by a 2023 research paper, GEO: Generative Engine Optimization, by Pranjal Aggarwal and colleagues. The researchers:

• Defined generative engines as systems that retrieve information from multiple sources and synthesize a response
• Proposed ways to measure a source's visibility inside those responses
• Built a benchmark of queries and tested content changes

Their key finding: some changes, such as adding citations from relevant sources, including quotations and adding statistics, tended to increase a source's visibility in generated answers, while traditional keyword stuffing didn't help. Effects varied by domain.

That's one study in a fast-moving field, using its own benchmark and engines of its time. It's a useful signal, not a rulebook.

How generative search assembles answers (at a high level)

Implementations differ and change, but generative search typically involves:

1. Understanding the question, sometimes breaking it into sub-questions. Google documents that AI Overviews and AI Mode may use a "query fan-out" technique, issuing multiple related searches across subtopics and data sources.
2. Retrieving sources from a search index, a partner's index or the system's own crawler.
3. Generating an answer with a language model, grounded in what was retrieved.
4. Attributing, by showing links or citations for some sources.

Each step suggests what helps: be findable (step 2), be relevant to sub-questions (step 1), be easy to use accurately (step 3) and be worth citing (step 4).

Verified facts vs emerging theories

Practical GEO

1. Make content citable

• Lead with a clear, quotable answer.
• Include specific facts, numbers and definitions, with sources.
• Use original insight: frameworks, observations, data you've gathered.
• Attribute quotations properly.

2. Strengthen entity clarity

Generative systems need to know who is speaking and what a business is. Use consistent names, descriptions and relationships across your website, profiles and listings. Mark up key entities with structured data that matches the visible page. On this site, for example, every page declares the same Person and Organization entities.

3. Earn corroboration

Generative answers tend to reflect what many reliable sources agree on. Mentions in reputable publications, industry sites, directories and reviews make your information easier to confirm.

4. Allow access deliberately

AI search products rely on crawlers. OpenAI, for example, documents separate controls: OAI-SearchBot for appearing in ChatGPT search results and GPTBot for model training, set independently in robots.txt. Decide what you allow on purpose. If you block search-oriented crawlers, you shouldn't expect to appear in those products' answers.

5. Keep facts current

Outdated information on your own site, or on profiles you control, can be repeated by AI systems. Update it.

6. Consider machine-readable summaries, without overestimating them

llms.txt is a proposed Markdown file summarizing a site for language models. It's cheap to add (this site has one), but it is a community proposal. No major provider has committed to using it for answers, so it's a convenience, not a lever.

GEO for local businesses

For local businesses, generative answers draw heavily on structured business information and reviews:

• An accurate, complete Google Business Profile and consistent listings elsewhere
• Genuine, descriptive reviews (reviews strategy)
• A website that states services, areas, prices or price guidance and credentials plainly
• Independent mentions in local media and associations

What GEO isn't

• Not a separate discipline from SEO. It depends on content being crawlable, indexable and trusted.
• Not manipulation. Hidden text, prompt-injection attempts and fake corroboration are deceptive and risky.
• Not guaranteed. Generative systems change frequently and make their own choices.

The takeaway

GEO is about being a reliable, citable, consistently described source when AI composes an answer. The research offers useful signals, the platforms document some mechanics, and the rest is still being learned. Build the foundations (clarity, accuracy, corroboration, access) and measure honestly. For the mechanics of how AI systems find businesses specifically, read how AI search engines discover and reference businesses.