GEO, AEO, and AI search optimization are often sold as a new set of secret requirements. Google's official position is more mundane: basic SEO practices remain relevant for appearing in AI features, with no separate mandatory schema or special AI file. A page must be indexable, crawlable, and contain useful text.

What is new is the form of competition more than the technical rules. A user asks a long question, and the system combines multiple sources into an answer. A superficial article repeating common knowledge loses to material with its own data, clear limitations, and a specific procedure.

Start with discoverability

Check the basics: the server returns 200 for an available page, robots.txt does not block the required crawler, the canonical points to the correct address, important text is present in the HTML, and internal links lead to the material through a clear hierarchy. For ChatGPT Search, OpenAI recommends not blocking OAI-SearchBot.

A sitemap helps discovery, but does not replace links. Structured data must match what the reader sees. Article or BlogPosting markup is useful as an accurate description of the page, rather than a way to tell search engines something absent from the text.

Write passages that can be verified

A good, citable passage answers one question without a haze of advertising. Start with a brief conclusion, followed by the conditions, method, and source. A dated table, a formula with variables, a step-by-step protocol, or an experiment description is more useful than a paragraph saying “we offer innovative world-class solutions.”

  • Specify the subject, period, and applicability of each fact.
  • Separate observation from interpretation and recommendation.
  • Link to a primary document, study, or your own methodology.
  • Update the date where prices, interfaces, or rules change.
  • Show limitations: when the conclusion does not apply and who it is unsuitable for.

Create original content rather than commodity content

In its guidance for generative search, Google emphasizes unique, non-commodity content: firsthand experience, a point of view, and material that cannot be obtained by simply reassembling search results. For a business, this means case studies with initial conditions, calculators with formulas, comparisons based on its own samples, interviews with practitioners, and analysis of mistakes.

Mass-producing pages for every wording of a question has the opposite effect: it duplicates intent, dilutes internal links, and adds text without new knowledge. One strong page covering the task and related clarifications is better than twenty weak variations on a title.

Entities must be consistent everywhere

Use consistent names for the company, product, author, and method. The “About us” page, author profiles, contacts, product listings, and external mentions should not describe different organizations. This is basic hygiene rather than a knowledge-graph trick: it makes it easier for readers and machines to connect a claim with an accountable source.

Authorship is especially important in topics involving risk. State who prepared the material, when it was updated, which sources it relies on, and how to report an error. Do not claim expertise without evidence. Transparent limits on trust are stronger than a decorative badge.

How to measure GEO without self-deception

Start with a set of real audience tasks, rather than one branded query. Once a month, record whether the page appears in ordinary search, whether an AI answer cites it, which passage is cited, whether visits follow, and what readers do. The query set must remain stable, or growth and decline cannot be compared.

  • Indexability and crawl errors.
  • Impressions and visits for topic pages.
  • Domain citations within a selected set of AI questions.
  • The share of mentions with an accurate fact and a link.
  • A useful action after the visit: reading, an inquiry, saving, or a purchase.

GEO works as the discipline of being a good source, rather than separate optimization: an accessible site, clear entities, original knowledge, verifiable statements, and regular updates. This is slower than generating a hundred pages, but it creates an asset useful to people and search engines alike.

How to structure a page that is easy to cite

Start with a specific question and a short answer, then explain the conditions, method, and exceptions. A number without a unit, period, and basis is almost useless: “conversion increased by 18%” does not say whether this is relative growth or percentage points, on what sample, or following which change. A table, formula, or sequence of actions should have labels, and the conclusion should reference observable data.

Do not hide the main claim inside an image, video, or interactive element. Provide a text equivalent, a proper heading, and a permanent URL. Connect internal links by meaning: a basic definition leads to a methodology, the methodology to a case study, and the case study to the source data. Article, Organization, and BreadcrumbList markup helps describe content already visible, but cannot compensate for a page without an answer.

The editorial update cycle

  • At publication, record the author, date, primary sources, and scope of applicability.
  • For changing topics, assign a review date and a person responsible for the fact.
  • When updating, explain what changed instead of silently replacing the conclusion.
  • Redirect a removed page to genuinely equivalent material.
  • Correct and acknowledge an error without creating a new copy of the same answer.

For measurement, keep a small register of twenty to thirty questions: informational, comparative, and branded. Check them in the same geography and mode, saving the date, cited passage, and landing page. Personalization and unstable AI answers prevent a single observation from counting as a ranking, but a series shows which formulations and sources the system consistently understands.