Generative Engine Optimization (GEO)

Generative engine optimization (GEO): being cited when AI answers your category

GEO is the work that makes your brand one of the sources a generative engine draws on and names when it writes an answer. We do it for B2B teams whose buyers now read a synthesized response with a short list of citations, and decide from that list who is worth a click.

The difference, plainly

AI search visibility has two halves. They share foundations and they measure different things.

AEO is about being the answer. One question in, one direct response out. The work is making your passage the one that response is built from. That lives on its own page: AEO.

GEO is about being cited. A generative engine reads many sources, writes a longer response in its own words, and lists where it drew from. GEO is the work that gets your brand into that source list, and named inside the response itself.

The practical difference: AEO asks "is our answer the one shown", GEO asks "are we one of the sources it used". Most teams need both, and we run them as one practice.

What we do

  • Entity optimization. We define the company, the product, the category and the people as entities, and make every mention on your site agree. A model that cannot resolve who you are will not cite you.
  • sameAs consolidation. We link your site to the profiles that describe you elsewhere with `sameAs`, so the references scattered across the web point back to one canonical entity.
  • Structured data. Organization, Service, Article, BreadcrumbList and FAQPage schema, matched to the visible page and validated. Service schema tells an engine what you actually sell. FAQPage schema hands it question and answer pairs it can quote.
  • Answer-first content architecture. Claims stated plainly and early, each one self contained, each one attributable to a source. Generative engines cite passages they can lift without ambiguity.
  • Source-grade content. We write the pages a model would reasonably draw from: definitions, comparisons, methods, and the original point of view only you can supply. Original material is what gets cited. Restated material is not.
  • Off-site consistency. We check that the descriptions of you sitting in third party profiles and directories match the entity on your site, and we list the mismatches for you to correct.
  • llms.txt. We write and publish an `llms.txt` file so AI crawlers know what your site contains and which pages are definitive.
  • Citation tracking. We run your category prompts against ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews on a schedule, record whether you were cited, in what context, and which sources appeared instead.

How we run it

We start with a written audit. We put your category prompts to each engine, capture the responses and the source lists, and read your site against what came back. You get a list: where you are cited, where you are not, what the engines say about your category today, and what to fix first.

Then we work in a rolling engagement, in this order.

  1. Set the entity. One definition, one name form, one category description, applied across the site and consolidated with `sameAs`.
  2. Add the schema. Organization and Service first, then Article and FAQPage as new pages ship.
  3. Restructure what exists. Answer-first openings, self contained claims, and headings that state the point rather than tease it.
  4. Publish `llms.txt` and confirm crawler access.
  5. Write source-grade pages. A rolling plan built on the gaps the prompt set exposed, weighted toward original material.
  6. Track and adjust. We re-run the prompts each month, log the citations, and change the plan based on what the engines actually did.

Each week you get a written update: what we shipped, what the tracking showed, what is next, and anything we need from you.

Deliverables

  • Written AI search visibility audit, with each engine's response and source list recorded
  • Entity definition and the site-wide consistency pass
  • `sameAs` consolidation and an off-site mismatch list
  • Structured data implemented and validated, including Service and FAQPage schema
  • Answer-first restructure of the existing pages
  • Published `llms.txt` and a crawler access check
  • New source-grade pages, written and published
  • Monthly citation tracking report across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews

Who it is for

  • B2B SaaS teams whose category is being explained to buyers by an AI answer that names someone else
  • AI startups defining a category that does not exist yet, and needing the models to learn the definition
  • Teams with real expertise and a thin published record of it
  • Marketing leaders who already run classic search work and want the AI half covered by the same people

Who it is not for

  • Teams wanting a promise of a citation. We do the work and we track what happens. No engine sells placement, and neither do we.
  • Sites with nothing original to say. Generative engines cite sources, and a page that restates the category is not a source.
  • Anyone with a broken crawl. Fix the foundation first: SEO.

Related services

  • AEO · being the answer inside answer engines and Google AI Overviews
  • SEO · the classic Google search foundation underneath
  • Website design · the pages this work sends people to

Questions we get asked

Find out what the engines say about your category today.

We review how you appear in Google search and in AI answers, then send you what we find in writing.

Start a project

Tell us what you are building.

Tell us where you want to go and we'll build the site that gets you there: fast, findable, and built to convert.