What Is GEO? Generative Engine Optimization Explained

Updated 26 October 2026. Written by the KIME CEO. Source data: KIME tracking data, Jul 26 to Oct 26 2026.

Generative engine optimization (GEO) is the practice of making your brand and content more likely to be retrieved, cited and accurately recommended in answers written by generative AI engines such as ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. In marketing, GEO means optimizing to be part of the answer itself, not only a link below it.

Below: where the term came from, how generative engines choose sources, core tactics, measurement and a worked example. For the comparison with classic search, read GEO vs SEO.

Key takeaways

• GEO stands for generative engine optimization: improving a brand's visibility, placement and accuracy inside AI-generated answers.

• The term comes from "GEO: Generative Engine Optimization" by Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan and Deshpande (Princeton and IIT Delhi), posted in November 2023 and published at KDD 2024.

• In the paper's 10,000-query benchmark, adding quotations, statistics and cited sources raised visibility by roughly 27% to 41%, while keyword stuffing lowered it.

• GEO methods helped lower-ranked pages most: citing sources raised visibility by 115.1% for the fifth-ranked source and reduced it by 30.3% for the top-ranked one.

• Generative engines combine model knowledge with live retrieval, so GEO covers crawler access, extractable content, evidence and third-party mentions.

• In KIME tracking data (Jul 26 to Oct 26 2026), AI answers drew on 3,622 domains, and listicles, comparison guides and structured explainers were the most cited page types.

• GEO is measured by running a fixed prompt set repeatedly across engines and tracking mentions, placement, sentiment and cited sources over time.

What is GEO? The meaning in marketing

Ask ChatGPT "which CRM should a 10-person agency use?" and you get a short written answer that names a few brands and cites a handful of pages. GEO is everything you do to influence that answer: whether your brand is named, where it appears, what the engine says about you and which pages it uses as evidence.

Three outcomes matter in GEO, and they are not the same thing:

• Mention: the answer names your brand.

• Citation: the answer links to one of your pages as a source.

• Recommendation: the answer suggests your brand as a good choice for the user's situation.

You can be cited without being recommended, and recommended without being cited. Together they make up your AI visibility. GEO is also called AI search optimization, LLMO or AI SEO, and it overlaps with answer engine optimization (AEO), the practice of formatting content as direct answers.

In short: GEO is about being named, cited and described correctly when an AI writes the answer, not about holding position one in a list.

Where the term GEO came from: the 2023 Princeton paper

"GEO: Generative Engine Optimization" was posted to arXiv on 16 November 2023 by Pranjal Aggarwal (IIT Delhi), Vishvak Murahari, Karthik Narasimhan and Ameet Deshpande (Princeton University), and Tanmay Rajpurohit and Ashwin Kalyan (independent researchers). It was published at KDD 2024, the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, held in Barcelona in August 2024.

The authors argued that generative engines take control away from content creators, because an answer can summarize a site without sending a visit. They built GEO-bench, a benchmark of 10,000 queries across many domains, and measured visibility as a position-adjusted word count (how much of the answer comes from a source, weighted by position) and a subjective impression score.

They tested nine ways of rewriting a source page. Results by position-adjusted word count against an unoptimized baseline:

Four findings still shape GEO practice:

• Evidence beats repetition. Adding substance worked; repeating keywords hurt.

• Lower-ranked pages gain the most. Citing sources lifted visibility by 115.1% for the fifth-ranked search result and cut it by 30.3% for the first, a real opening for challengers.

• It worked on a live engine. On Perplexity, the authors reported visibility gains of up to 37%.

• Domain matters. Statistics helped most for law, government and opinion queries; quotations for people, society and history. Fluency plus statistics was the best pair tested.

Keep the limits in mind: the study used 2023-era models and a controlled benchmark, and it measured text visibility, not brand recommendations. Treat it as direction, not a guaranteed uplift.

How does generative engine optimization work?

GEO works by influencing each step a generative engine takes to pick its sources and write an answer. For the engine side in more depth, see what AI search is and how it works.

Two consequences follow. If a crawler cannot reach your page, stages 3 to 5 never happen: OpenAI says sites blocking OAI-SearchBot will not appear in ChatGPT search answers, and Google requires pages to be indexed and snippet-eligible for its AI features. And the engine reads many sites, not just yours. In KIME tracking data, corporate and vendor sites were 46% of source uses; review marketplaces (12.5%), competing vendors (9.2%), affiliates (7.4%), news (6.8%), social (3.3%) and communities (2.8%) supplied much of the rest.

In short: generative engines retrieve, select and summarize. GEO makes your pages easy to retrieve, easy to quote and consistent with what the rest of the web says about you.

Core GEO tactics

These tactics work across the ten engines KIME tracks; each links to a deeper guide.

1. Open the door to AI crawlers. Allow OAI-SearchBot, PerplexityBot, Googlebot and Bingbot in robots.txt and firewall rules, and make key content render without heavy JavaScript (see agent readiness).

2. Write extractable, answer-first sections. One idea per section, a direct answer first, descriptive headings (see structuring content for LLM extraction).

3. Add evidence. Sourced statistics, short expert quotes and primary-source citations: the strongest methods in the GEO paper.

4. Publish the formats engines cite. In our data, listicles, comparison guides and structured explainers were cited most.

5. Keep your entity consistent. Same name, category, facts and pricing on your site, schema, profiles and directories. Our AI information page is one example.

6. Earn third-party mentions. Target the review platforms, roundups and communities already cited for your prompts.

7. Refresh and monitor. Date your facts and watch for shifts; engines change trusted sources quickly (see URL volatility).

The full playbook is in how to get cited by AI search; engine guides include ChatGPT and Google AI Overviews.

GEO examples

• Fixing a wrong fact. A SaaS brand sees engines quoting last year's price, traces it to a cited review profile, and updates that profile plus a dated pricing table on its own site.

• Winning a comparison prompt. A challenger absent from "X vs Y" answers publishes a fair, sourced comparison page that engines start citing.

• Getting into the shortlist. An ecommerce brand finds three affiliate roundups cited for its category prompt and sends those publishers samples and current specs.

How to measure GEO

Answers have no fixed positions and change between runs, so measure GEO by running a fixed prompt set repeatedly across engines and markets and recording what each answer says.

Google Search Console folds AI Overviews and AI Mode into overall web search data, so those need prompt-based tracking too. See our guides to tracking AI visibility across AI search engines and connecting AI visibility to revenue.

Worked example: a GEO cycle for a B2B brand

A fictional project management tool, Taskhaven, sells to agencies in the US, UK and Denmark. The numbers are illustrative; the workflow is the one we run with customers.

1. Build the prompt set. 30 prompts across category ("best project management tool for agencies"), comparison ("Taskhaven vs Asana") and problem ("how to track billable hours") intents, run daily in three markets on five engines.

2. Set the baseline (two weeks). Taskhaven appears in 9% of answers, usually fourth or fifth. Two engines wrongly call it "for small teams only".

3. Analyze sources. Category answers cite two review marketplaces, three "best tools" listicles, a Reddit thread and a competitor comparison page. Only Taskhaven's homepage is cited.

4. Act on site. Add a dated "who it is for" table to the homepage, publish fair comparison pages, and add original statistics and a customer quote to the billable-hours guide.

5. Act off site. Update both review profiles, send current facts to the listicle authors, and answer the Reddit thread openly.

6. Re-measure (eight weeks). Compare presence, placement, sentiment and the outdated claim with the baseline, and check which new URLs are cited.

The biggest lift rarely comes from one page; it comes from fixing the sources engines already trust.

GEO vs SEO in one paragraph

SEO earns rankings and clicks in search results; GEO earns mentions, citations and recommendations inside AI answers. GEO is built on SEO foundations (crawlable, indexed, helpful pages) and adds prompt tracking, evidence-rich passages, off-site source work and new metrics. The full comparison is in GEO vs SEO.

How KIME supports GEO

KIME is a GEO platform from Copenhagen. It tracks prompts by category and market across ten engines (see integrations), and reports visibility, placement, share of voice, sentiment and citation analysis by domain and URL. The Action Center turns gaps into tasks, and AI Site Health checks whether AI crawlers can reach and extract your pages.

Frequently asked questions

What is GEO in marketing?

GEO in marketing means generative engine optimization: improving how often and how accurately AI engines such as ChatGPT, Perplexity, Gemini and Google AI Overviews mention, cite and recommend your brand. It combines content work, technical access for AI crawlers and off-site reputation, and it is measured with visibility, share of voice, sentiment and citations rather than rankings alone.

What does GEO stand for?

GEO stands for generative engine optimization. The term was popularized by a 2023 paper by Aggarwal and colleagues from Princeton University and IIT Delhi, published at KDD 2024. In some contexts GEO also means geographic targeting, so in AI search discussions it is often written out in full the first time it is used.

How does generative engine optimization work?

Generative engine optimization works by influencing each step an AI engine takes to answer a question. Engines rewrite the prompt into searches, retrieve pages from an index, select the most useful passages and write a summarized answer with citations. GEO makes your pages reachable by AI crawlers, easy to quote, rich in evidence and consistent with what third-party sites say about you.

Who invented generative engine optimization?

Generative engine optimization was introduced as a research framework by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande. Their paper, "GEO: Generative Engine Optimization", was posted to arXiv in November 2023 and published at KDD 2024. It introduced the GEO-bench benchmark of 10,000 queries.

What are examples of GEO?

Examples of GEO include adding sourced statistics and expert quotes to a key page, publishing fair comparison pages, correcting an outdated price on a review profile that AI engines cite, pitching current facts to the listicles that appear in AI answers, and unblocking AI crawlers in robots.txt. Each one targets a step in how engines retrieve and summarize sources.

How do you measure GEO?

You measure GEO by running a fixed set of prompts repeatedly across AI engines and markets, then tracking how often your brand is mentioned, where it appears, how it is described and which sources are cited. Add AI referral traffic from analytics. Judge trends over several weeks, because individual AI answers vary from run to run.

Why is GEO important?

GEO is important because more buyers now get answers from AI engines instead of clicking search results. Pew Research found Google users clicked a traditional result in 8% of visits when an AI summary appeared, versus 15% without one. If AI answers name competitors and not you, you lose consideration before a buyer ever reaches your site.

Does keyword stuffing work for GEO?

No, keyword stuffing does not work for GEO. In the original GEO study, repeating query keywords was the only tested method that reduced visibility in generative answers, by about 8% on the main benchmark. Methods that added substance, such as quotations, statistics and cited sources, performed best. Write for clarity and evidence, not repetition.

Related guides

• GEO vs SEO: differences, overlap and how to run both

• What is AEO? Answer engine optimization explained

• What is AI visibility?

• How to get cited by AI search

• Topic clusters for GEO

• The Ecommerce GEO Playbook

Sources: KIME tracking data, Jul 26 to Oct 26 2026 · Aggarwal et al., GEO: Generative Engine Optimization (arXiv) · Princeton University: GEO publication record (KDD 2024) · Google Search Central: AI features and your website · OpenAI: Overview of OpenAI crawlers · OpenAI Help Center: ChatGPT search · OpenAI Help Center: Publishers and developers FAQ · Search Engine Land: Bing Webmaster Tools AI Performance report · Pew Research Center: Google users and AI summaries