GEO, AEO and SEO: differences and a practical plan

What do GEO, AEO and SEO mean?

GEO, AEO and SEO describe overlapping ways to help people discover and understand your business. The terms can make planning feel complicated. A useful starting point is the buyer’s question: what information would help someone choose confidently?

Search engine optimization, or SEO, helps search engines discover and interpret pages that serve that need. Answer engine optimization, or AEO, focuses on making information useful as a direct answer. Generative engine optimization, or GEO, examines how sources and brands appear in generated responses.

AEO and GEO are industry labels with varying definitions. Before commissioning work, ask what the provider will change, observe and report. Agreeing on those deliverables matters more than choosing a preferred acronym.

Start with the foundation all three share

A strong website explains who an offer serves, what it includes and where its limits lie. It also makes that information easy to reach. Clear navigation and meaningful links help visitors move from an introduction to the evidence behind it.

Google’s SEO Starter Guide explains the basics of making content discoverable and understandable. Use those fundamentals to review important pages before adding new publishing tools or reporting systems.

For example, a payment provider could clarify which terminals support an unattended retail setup. The page should cover compatibility, installation requirements and support options. That single improvement helps a buyer evaluate the product and gives search systems clearer information to interpret.

Add the generated answer to your review

Traditional search reporting often starts with queries, landing pages and visits. An AI visibility review also looks at the answer itself. Does it name the brand? Does it describe the offering accurately? Does it link to a useful source?

These observations mean different things. An assistant might mention a company while recommending another supplier. It might cite a technical guide without discussing the company’s services. Treating either event as a lead would make the report misleading.

Keep a record of the question, response and source links. Our guide to AI visibility measurement explains how to define these measures and report the limits of a sample.

Keep technical access on the checklist

For Google’s AI Overviews and AI Mode, pages must be indexed and eligible to appear with a search snippet. Google’s guidance for AI search features says there are no additional technical requirements or special schema types for inclusion.

That guidance applies to Google’s features. Other providers have their own access controls and documentation. Review the providers that matter to your audience before changing crawler rules across the whole site.

Start by checking your important pages: can a visitor reach them, read the main content and follow related links? Then review indexing controls and canonical URLs. Our explanation of robots.txt, sitemap.xml and llms.txt helps separate the purpose of each file.

Choose content from actual buying questions

Collect questions from sales calls, support requests, product demonstrations and customer research. Group them by the decision they support. Questions about price, compatibility, implementation and alternatives often need different evidence.

Next, map each group to an existing page. Improve a page when it already serves the right purpose. Create a new one when the reader needs a distinct answer. This approach gives each URL a clear job and reduces repeated content.

A buyer comparing two approaches may need a concise comparison with clear tradeoffs. A buyer planning implementation may need prerequisites and a realistic sequence. Use the citable content checklist to check the clarity and support behind each answer.

Run a focused first improvement cycle

Give the first cycle a clear owner and a manageable scope. A small set of well-supported updates is easier to review than a large batch of thin pages. Record what changed so later observations have context.

For a hypothetical software company, that cycle might cover one product page and one comparison guide. The team could add supported integrations, explain migration steps and document who the product suits. It would then review the same buyer questions again.

• Define the audience, market and decisions you want to support.
• Save a baseline of search performance and a documented answer sample.
• Choose pages with a clear information gap and business purpose.
• Add evidence, relevant internal links and a useful next action.
• Publish the changes, record their dates and schedule a review.

Measure progress with clear expectations

Agree on measures before work starts. Search visits, sampled mentions, owned citations and qualified inquiries each answer a different question. Report them separately, with dates and definitions, so the team can understand what improved.

No provider can promise control over an independent assistant’s recommendation. A useful engagement instead specifies the research, technical changes, content improvements and reporting it will deliver. Early results may identify a missing explanation before they show a change in inquiries.

Start with one important buyer journey and improve it end to end. Citevia’s methodology connects that research to content and measurement. The aim is a site people can use and trust, supported by evidence your team can explain.