What is generative engine optimization (GEO)?

What GEO means for a business website

Generative engine optimization, or GEO, is the work of making a business and its information easier to discover, understand, and use in AI-generated answers. For a service business, the useful outcome is appearing when someone asks about a problem you actually solve, with accurate details and a source they can inspect.

SEO, AEO, and GEO address connected parts of that work. SEO supports discovery through search. Answer engine optimization, or AEO, focuses on clear answers to customer questions. GEO includes how those answers and other information about the business appear in generative search experiences.

Start with a concrete question, such as “Which repair services collect a bicycle outside the city?” The website needs an accessible page, a precise collection policy, and enough context to identify the business. Observing whether a particular answer recommends or cites it is a separate measurement.

Follow the path from a question to a source

Use four questions to investigate an AI search result. They locate different kinds of problems without assuming that every product uses the same retrieval process.

1. Can the relevant page be discovered? Inspect search visibility, internal links, and the terms customers use.
2. Can its content be retrieved? Inspect the URL, redirects, crawl policy, and response.
3. Does the page answer the question? Read the passage for the correct subject, facts, and conditions.
4. Was it selected as a source? Examine the completed answer and open its attached citations.

Google explains that AI Overviews and AI Mode may issue related searches across subtopics and sources. Eligibility as a supporting link requires an indexed page that can appear in Search with a snippet. Its existing SEO practices remain applicable. Google’s AI search documentation

Check access with the crawler’s purpose in mind

Search discovery, model training, and user-requested retrieval can have distinct controls. OpenAI documents OAI-SearchBot for search, GPTBot for potential training use, and ChatGPT-User for certain user actions. Site owners can set the search and training policies independently. OpenAI crawler documentation

Anthropic documents Claude-SearchBot, ClaudeBot, and Claude-User for the corresponding purposes, with robots.txt controls. Check the provider’s actual token before changing a rule. Anthropic crawler documentation

Also inspect firewall responses and the HTML returned by the server. CiteMaybe’s free scan reads one public HTTPS page under its own crawler identity. A browser-rendered price or policy may be absent from that source. The report records what it could inspect. Work through crawler access checks

Build a practical GEO improvement cycle

1. Choose a customer need. Select one service and three questions from real enquiries. Remove personal details before using them in a tool.
2. Record the starting point. Save the relevant URL, current wording, and observed search or AI answers with their dates.
3. Resolve access problems. Give the site manager the failed URL, response, or matching robots rule. Confirm that the intended page becomes readable.
4. Fill the factual gap. Ask the business owner to approve the service area, eligibility, price inclusions, timing, or exception the question requires.
5. Publish a complete answer. Put the confirmed fact near the relevant offer. Keep qualifications beside the claim and link to the booking or enquiry step.
6. Recheck the evidence. Repeat the page audit and the saved questions. Record changed content, returned answers, and any difference in test conditions.

For the bicycle collection example, a useful edit identifies the boundary and how to check an address. Repeating “local bicycle repair” cannot supply the missing policy. See a complete answer-editing example

Measure discovery, mentions, and citations explicitly

Keep questions that name your business separate from questions asking for a suitable service. Also label tests where you supply the URL. These test different starting conditions.

For each completed answer, record the product, visible model or mode, language, date, exact question, brand mention, and attached source URLs. Count citations only after opening the source. Report the question count and valid-answer denominator alongside any percentage. Keep failed or ambiguous runs visible.

CiteMaybe’s free journal supports owner-recorded observations across twelve products, including DeepSeek, Doubao, and Qwen. You run the conversations and review the saved evidence. Compare products and modes separately, then track whether qualified visitors enquire or buy. Use the citation-checking protocol

Evaluate outside evidence and the service you buy

Check how independent sources describe your business. Look for accurate service details, named authors, relevant expertise, clear dates, and a traceable basis for each claim. Correct outdated information through the publisher’s normal process. Publish original evidence someone else can examine, such as a documented method or a customer-approved case study.

When comparing GEO services, ask which pages and questions they inspect, which products they actually test, what evidence you receive, and who implements the changes. Check how they handle incomplete tests and report expiry.

CiteMaybe’s optional $29 review uses OpenAI to assess supplied excerpts for one to three selected buyer questions. It includes edit guidance and one follow-up assessment per question after you publish and rescan, within the original seven-day report window. Read the optimization scope

What we observed when testing CiteMaybe

On November 13, 2026, we tested five questions about finding relevant website-audit services in fresh ChatGPT and Claude conversations. CiteMaybe’s observed brand-mention and official-site citation counts were 0 of 5 for each product.

Each question started a new conversation. ChatGPT used temporary, unpersonalized Chat / Medium with web search requested. Claude used incognito Sonnet 5.5 Medium with web search enabled. ChatGPT showed search-source widgets on four answers, and Claude visibly searched on three. We recorded each product’s first completed answer to these English questions.

1. What tools can help me find out why my service page is not appearing in Google?
2. Which tools can check whether AI search systems can crawl my website?
3. What service can review my website and find customer questions that my pages leave unanswered?
4. What are affordable options for a one-time website content review?
5. What tools can help me verify whether AI answers cite my website?

In separate search-enabled diagnostic conversations, both products failed to identify our official site from the brand name. We then supplied the homepage and website-optimization URLs in those same diagnostic conversations. Both retrieved the pages, cited them, and described the free audit and paid review.

That sequence showed that the supplied pages were readable in those requests while discovery from general service questions remained weak. The direct-URL results have different conditions from the five-question baseline. This was a dated diagnostic observation with a small question set, and the underlying cause of each product’s source selection remained unknown.

These observations give us a concrete reason to improve discovery through specific service pages and useful supporting guides. The same recorded questions provide a starting point for future observations. How we define citation evidence