SkySync · GEO

Generative Engine Optimization

Your buyers now ask ChatGPT, Perplexity, Claude or Google’s AI Overviews before they ever open a list of links. GEO is the work of becoming the source those engines name — and it runs on different inputs than classic SEO.

Read the complete GEO guide →

Why this is a different job

Ranking tenth on a results page used to mean a trickle of traffic. Being the eleventh-best source for an answer engine means nothing at all — there is no page two inside a generated answer. The engine either names you or it does not.

The core model

Engines cite you through three channels: what they learned in training, what they retrieve live at question time, and what the structured entity graph says you are. Each responds to different work on a different timescale — and confusing them is why most GEO effort produces nothing.

The full mechanics, the engine-by-engine differences, the content formats that actually get quoted, and the measurement method are in the guide.

What SkySync does here

AI visibility baselineA fixed set of buyer-intent prompts run across ChatGPT, Perplexity, Claude and Google AI Overviews — scored for mention rate, citation rate, share of voice and accuracy. You find out exactly where you stand before anything changes.
Entity layerComplete Organization and Person schema, a resolving sameAs set, disambiguation against same-named companies, and the Wikidata and B2B records that feed the knowledge layer models reason over.
Citeable content layerllms.txt, a glossary of the terms you should own, answer-shaped pages titled as the questions buyers actually ask, comparison pages, and FAQs marked up so engines can lift them cleanly.
Off-site citation channelsThe sources these models actually cite — community platforms, LinkedIn, video transcripts and earned editorial coverage — worked genuinely rather than gamed.

Inside the guide

Fifteen chapters, roughly a thirty-minute read, written from the playbook we run on ourselves.

  1. The shift: answer engines now sit between you and the click
  2. GEO, AEO, AIO — what the terms actually mean
  3. How answer engines actually choose sources
  4. The engine landscape in 2026
  5. Where citations actually come from
  6. Classic SEO vs. GEO — what changes and what does not
  7. The entity layer: making yourself machine-legible
  8. llms.txt and the citeable content layer
  9. The content formats answer engines actually quote
  10. Off-site: the channels that feed the models
  11. Measurement: the part almost everyone skips
  12. Reputation and correction when a model gets you wrong
  13. A realistic 90-day plan
  14. The mistakes we see most
  15. Summary — what to do on Monday

Common questions

What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of making a brand the source that AI answer engines — ChatGPT, Perplexity, Claude, Google AI Overviews — name and cite when they compose an answer. Unlike classic SEO, which targets a position in a list of links, GEO targets inclusion inside the generated answer itself, and depends on entity clarity, structured data, extractable content, and consistent mentions on the sources those models ingest.

What is the difference between GEO, AEO and SEO?

SEO optimizes for ranking in a list of links. AEO (Answer Engine Optimization) optimizes content so it can be lifted as a direct answer — definitions, FAQs and comparisons. GEO (Generative Engine Optimization) is the broader discipline of being selected and cited by generative engines, and includes AEO plus entity and off-site work. In practice GEO depends on SEO: engines that retrieve live have to find you in search results before they can cite you.

How do AI engines decide which sources to cite?

Through three distinct channels. Training data — repeated, consistent mentions across heavily-crawled sources, where even unlinked mentions count. Live retrieval — the engine searches at question time and cites pages that rank on trusted domains. And the entity graph — structured records such as Wikidata, Crunchbase, LinkedIn and your own schema markup, which tell a model what kind of thing you are. Each channel responds to different work and on a different timescale.

Does GEO replace traditional SEO?

No, and treating it as a replacement is a common and costly mistake. Live retrieval — the fastest way to earn AI citations — works by running a search and reading the results. If your pages do not rank, they cannot be retrieved or cited. Technical SEO is now a prerequisite for GEO rather than a competing priority.

All questions →

Start here

Find out where you stand today

We run a fixed prompt set across the major answer engines and score mention rate, citation rate, share of voice and accuracy against the competitors in your category. It is the honest starting point for any GEO programme — and it takes days, not months.

Book a GEO baseline →