What is generative engine optimization?

By Seedcite. Published . 5 min read.

Generative engine optimization (GEO) is the practice of making your content easy for AI answer engines such as ChatGPT, Perplexity, Gemini and Google's AI features to find, understand and cite. It builds on SEO rather than replacing it. The one academic benchmark we found reports visibility gains of up to 40% on its test set, but that does not prove the same effect on today's assistants.

Illustration of a plant that grows into a source card marked as cited.
Illustration. A page grows from the ground, and the answer card beside it names it as a source.

Many different seeds and tiny seedlings scattered in a loose band.

What is generative engine optimization?

Generative engine optimization, usually shortened to GEO, is the work of making your pages easy for AI answer engines to find, understand and quote. Those engines include ChatGPT, Perplexity, Gemini and the AI features inside Google Search. The goal is to be one of the sources named or linked when one of them writes an answer.

The term comes from academic work. A research paper first presented at KDD 2024 defined "generative engines" as search systems that read many sources and write one synthesized answer, then tested ways for publishers to raise their visibility inside those answers (arXiv 2311.09735).

The idea is simple. A classic search result gives a reader ten links. An answer engine gives one paragraph and a short list of sources. Being in that list is the new version of being on page one.

How is GEO different from SEO and AEO?

GEO sits on top of SEO rather than replacing it. SEO is about being crawled, indexed and ranked in a list of results. AEO, answer engine optimization, is about being the short answer a search page or assistant reads out. GEO is about being cited inside a generated answer. In practice the three terms overlap, and the same page can serve all of them.

The useful distinction is what you measure. For SEO you watch clicks and positions. For GEO you watch whether an engine names or links your page when someone asks a question your buyers ask. A page can rank well and still not be cited, which is why the second measurement is worth having.

These definitions are ours. The industry has not settled on strict meanings, so expect other writers to draw the lines in different places.

What does the research actually show?

Less than the headlines suggest. The Princeton-led GEO study reports in its abstract that its methods can boost visibility by up to 40% in generative engine responses on its benchmark. That is a real result on a specific test set. It is not proof that the same tactics lift your citations in today's ChatGPT or Perplexity, and the paper's per-tactic numbers (for example for adding citations, quotations or statistics) are ones we could not confirm because we could not reach the full text.

Several figures circulate about how often AI answers cite pages that also rank in Google's top ten. A secondary source reports that Ahrefs measured 76.1% in July 2025, falling to about 37.9% by March 2026 (almcorp.com). Other reports put the overlap for conversational assistants far lower, around 12% from Ahrefs and about 17% from BrightEdge, with Perplexity at 28.6%. We could not verify any of these at a primary source, so treat them as direction, not fact.

What survives all of that uncertainty is one practical point: a top-ten ranking does not guarantee an AI citation. Treat the two as related but separate outcomes.

A top-ten ranking does not guarantee an AI citation.

Do you need llms.txt or special markup?

For Google's AI features, no. Google's documentation says these features need no special markup, no llms.txt file, no AI text file and no special schema. It advises keeping important content as text and making sure structured data matches what is visible on the page (Google Search Central, AI features).

For other engines the picture is murkier. Adoption of llms.txt is rising, with one count reporting 4,088 files in June 2025 and 36,120 in May 2026, but the same coverage cites a log analysis finding roughly 97% of those files received zero AI-crawler requests (ppc.land). A separate report says SE Ranking found no significant link between having the file and being cited (digitalapplied.com). All of those figures are secondary and unverified.

Our read: the file is cheap and harmless, and nothing we found shows it improves citations. Do it after the basics, not instead of them.

What should a small site do first?

Start with habits that help readers, because they are also what a system looking for a quotable answer needs. None of the items below has a verified effect size. They are our interpretation of the evidence above, and you should test them rather than trust them.

  • Put the direct answer in the first one or two sentences under each question heading, then explain.
  • Write headings as the questions your buyers actually ask.
  • State facts you can source, and link to the source. Do not invent statistics or quotes.
  • Keep key content as visible text. If you add FAQ structured data, make it match the visible text exactly.
  • Link related pages with ordinary crawlable links, which Google says help it discover pages and understand your site structure (Google Search Central, crawlable links, wording not re-fetched by us).
  • Add first-hand detail that nobody else has: your process, your numbers, your photos.

How do you measure whether GEO is working?

There is no standard method that we found, so this section is design guidance rather than a sourced procedure. The most defensible approach is a fixed prompt panel.

  1. Write 50 to 200 prompts that match what your buyers ask, and keep the list fixed.
  2. Run every prompt on each engine several times, because answers vary from run to run.
  3. Log every cited URL and every mention of your brand.
  4. Compute share of voice: your citations divided by all citations across you and your competitor set.
  5. Report the run count and the variance next to every number.

Small movements inside the variance are noise. Look for sustained shifts over several weeks, and compare against a baseline you recorded before you changed anything.

Sources

  1. Abstract onlyAggarwal et al., GEO: Generative Engine Optimization (arXiv, KDD 2024) https://arxiv.org/abs/2311.09735
  2. Checked 2026-10-20Google Search Central: AI features and your website https://developers.google.com/search/docs/appearance/ai-features
  3. Unverified, wording not fetchedGoogle Search Central: crawlable links https://developers.google.com/search/docs/crawling-indexing/links-crawlable
  4. Unverified, secondaryalmcorp.com on AI Overview citations vs. top-ranking pages https://almcorp.com/blog/google-ai-overview-citations-drop-top-ranking-pages-2026/
  5. Unverified, secondaryppc.land on llms.txt adoption https://ppc.land/llms-txt-adoption-rises-8-8x-but-97-of-files-get-zero-ai-requests/
  6. Unverified, secondarydigitalapplied.com on llms.txt in practice https://www.digitalapplied.com/blog/llms-txt-in-practice-adoption-evidence-2026

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