Generative engine optimization (GEO) is the work of making your brand’s content more likely to be retrieved, quoted, and cited when AI systems such as ChatGPT search, Google AI Overviews and AI Mode, Perplexity, and Copilot generate an answer. It builds on SEO rather than replacing it: a page still has to be crawlable and indexed before an AI engine can use it. GEO adds a second question on top of “do we rank?”: “when an AI writes the answer, is our evidence part of it?”
This guide covers where GEO came from, what the research actually shows, how the major engines decide what to cite, and how to run a GEO program a CFO would sign off on.
Where the term “generative engine optimization” comes from
The term was formalized in a 2023 research paper, GEO: Generative Engine Optimization, by researchers from Princeton, Georgia Tech, the Allen Institute for AI, and IIT Delhi, later accepted to KDD 2024. The authors define “generative engines” as search systems that gather information from multiple sources and summarize it with a large language model. Their concern was the third party in that exchange: the website owner, who has little control over when or how their content shows up in the answer.
That framing is still the most useful one for brands. In a generative answer, you are not competing for a position on a page of links. You are competing to be one of the few sources the model leans on, and for how much of your content makes it into the response.
What the GEO research found (and what it didn’t)
The researchers built a benchmark of 10,000 queries and tested nine ways of rewriting source content. Three findings matter for marketers:
- Evidence beat keywords. Adding citations from credible sources, adding relevant quotations, and adding statistics were the top-performing methods, improving visibility by roughly 30–40% on the paper’s main metric. Keyword stuffing, the classic SEO shortcut, did not perform well.
- Results varied by domain. The authors note that what works depends on the subject and query type, which argues for testing in your own category rather than applying a universal checklist.
- Lower-ranked pages gained the most. In their experiments, pages ranked lower in traditional results benefited more from these changes than the top result did.
Two cautions keep this honest. First, these were controlled experiments on a benchmark (with a smaller test on Perplexity), not a guarantee of how any engine behaves today. Second, “add statistics” means adding real, sourced numbers. Fabricated or unsupported figures damage trust with buyers and create risk for your brand, whatever they do for visibility.
How generative engines decide what to cite
Every major engine follows a similar pattern: retrieve candidate pages from a search index, then generate an answer grounded in some of them. The practical implications differ slightly by platform.
Google AI Overviews and AI Mode
Google’s guidance on AI features is direct: there are no additional requirements or special optimizations needed to appear, and no special schema or “AI text files” are required. To be eligible as a supporting link, a page must be indexed and eligible to show with a snippet. Google also explains that both features may use “query fan-out,” running multiple related searches across subtopics to build a response. That rewards brands that cover a topic thoroughly, not ones that own one phrase.
ChatGPT search
OpenAI documents its crawlers separately. OAI-SearchBot is used to surface websites in ChatGPT’s search features, and sites that opt out of it will not be shown in ChatGPT search answers. GPTBot is a separate control for model training. A brand can allow one and block the other.
Perplexity
Perplexity’s crawler documentation describes PerplexityBot as the agent that surfaces and links websites in its search results, and recommends allowing it in robots.txt and permitting its published IP ranges if you use a web application firewall.
| Engine | What controls eligibility | What to check first |
|---|---|---|
| Google AI Overviews / AI Mode | Standard Google indexing and snippet eligibility | Indexing in Search Console, nosnippet controls, structured data matching visible text |
| ChatGPT search | OAI-SearchBot access | robots.txt, CDN and firewall rules blocking OpenAI’s IP ranges |
| Perplexity | PerplexityBot access | robots.txt and WAF allowlists for Perplexity’s published IPs |
In audits, the most common GEO problem is not content at all. It is a security or bot-management setting quietly blocking an AI search crawler the brand actually wants.
GEO vs. SEO vs. AEO
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | Rank pages in search results | Win direct answers (featured snippets, voice) | Be retrieved and cited inside AI-generated answers |
| Unit of competition | The page | The single best answer | The passage, the claim, and the brand entity |
| Main levers | Technical health, relevance, links | Concise, question-led formatting | Access for AI crawlers, topic coverage, verifiable evidence, consistent brand data |
| Success metric | Rankings, clicks | Snippet ownership | Mentions, citations, AI referrals, assisted revenue |
In practice the labels overlap, and you will hear AI SEO and AI search optimization used for the same work. We covered how agencies package it in What does an AI SEO agency actually do? The point here is that GEO doesn’t replace the SEO foundation; it raises the bar on evidence and coverage.
The SAMA view: build a question portfolio, not a keyword list
We come from building and scaling our own brands, and we judge marketing against contribution margin and payback rather than platform-reported numbers. Applied to GEO, that leads to one rule: prioritize the questions that sit closest to revenue, not the ones that look biggest.
Our working method treats GEO like an investment portfolio:
- 1. Map the question set. List the 30–50 questions buyers ask before choosing a product like yours: comparisons, “best for” queries, price and quality objections, compatibility, and “is it worth it” questions.
- 2. Weight by margin, not volume. A question that leads to your highest-margin product line or a strong repeat-purchase customer is worth more than a broad informational question with more searches.
- 3. Score your evidence per question. For each question, ask whether there is a page that answers it in the first few sentences, backs it with specifics (specs, sourced data, expert input, real reviews), and is corroborated off-site by marketplaces, reviews, or press.
- 4. Close the biggest gaps first. Fix access and data conflicts, then strengthen the pages for high-value questions, then expand coverage.
- 5. Re-measure monthly. Track the same question set across engines so you can see movement rather than anecdotes.
This keeps GEO tied to the business. A brand that is cited for fifty informational questions but missing from the three comparison questions that drive purchases has a visibility report, not a growth result.
A practical GEO checklist for brands
- Access: Allow Googlebot, OAI-SearchBot, and PerplexityBot where you want visibility, and check CDN and firewall rules, not just robots.txt.
- Answer first: Open each key page or section with a direct answer, then support it. Each section should make sense if quoted on its own.
- Evidence: Cite primary sources, use real data you can stand behind, and add expert or customer perspective you can verify.
- Entity consistency: Keep product names, specs, prices, and company details identical across your site, feeds, marketplaces, and structured data. We explain why in our e-commerce AI SEO/GEO priorities.
- Topic coverage: Build clusters that answer the follow-up questions a fan-out search would ask, not single pages for single phrases.
- Measurement: Combine Search Console data (Google reports AI Overviews and AI Mode traffic within the Web search type), analytics referrals from AI platforms, and a recurring manual or tool-based check of your question set.
GEO also works better when it is connected to the rest of your growth system. Paid search data shows which questions convert, retention programs bring back AI-referred first-time buyers, and marketplace listings are often the product source AI engines rely on. That is why we run AI search optimization alongside SEO, paid media, retention, and marketplaces.
Frequently asked questions
Is generative engine optimization replacing SEO?
No. Google states that SEO best practices remain relevant for its AI features, and pages must be indexed to be eligible as supporting links. GEO is a layer on top of SEO that focuses on citation and evidence inside AI answers.
Do I need special schema or an llms.txt file for GEO?
Not for Google. Its guidance says no new machine-readable files, AI text files, or special schema are needed for AI Overviews or AI Mode. Structured data still helps search engines understand your pages, provided it matches the visible content.
How long does GEO take to show results?
It depends on how fast technical fixes ship, how often engines recrawl your pages, and how competitive your category is. Access problems can be fixed quickly; earning citations for competitive comparison questions usually takes sustained content and corroboration work. Be wary of fixed-date promises.
Can anyone guarantee my brand will be cited by ChatGPT or Google AI?
No. Google says meeting its requirements doesn’t guarantee crawling, indexing, or serving, and AI answers vary by query and platform. A credible GEO partner commits to the work and to transparent measurement, not to placements.
How do I know where my brand stands today?
Run your top buyer questions through ChatGPT, Google AI Mode, and Perplexity and record who is mentioned and cited. If competitors appear and you don’t, or the answers describe your products incorrectly, you have a measurable starting point. Our guide to getting recommended by ChatGPT and other AI search engines shows how to turn those gaps into a fix list.
The bottom line
Generative engine optimization is about earning a place in the answer, not just the results page. Start by confirming AI crawlers can reach you, then focus your content and evidence on the buyer questions closest to revenue, and measure the same question set every month. Brands that treat GEO as a margin-weighted portfolio, not a new keyword list, get a clearer return on the effort.
Not sure how AI engines describe your brand right now? SAMA Labs runs AI visibility audits for e-commerce and growth-stage brands that show which buyer questions you are cited for, where competitors appear instead, and what to fix first. Book your AI visibility audit.