What Is Generative Engine Optimization (GEO)?

Buyers have started asking AI instead of searching. They open ChatGPT or Perplexity, describe what they need, and read the answer the model gives them. Most of the time they never click a single link. The brands the model names in that answer get the consideration. Everyone else is invisible, no matter how well they rank on Google.

GEO is how you get named. It is the work of making sure that when someone asks an AI engine the questions your customers actually ask, your brand is the one it cites.

Why GEO matters now

The shift is already here. A large and growing share of searches end without a click, because the answer is shown directly. Hundreds of millions of people use ChatGPT every week, and tools like Perplexity field hundreds of millions of queries a month. For a buyer comparing tools, the AI answer is often the first shortlist they ever see.

If your competitors are named in that answer and you are not, you are losing deals before a salesperson is ever involved. The buyer simply never learns you exist.

How GEO is different from SEO

SEO and GEO both want visibility, but they play different games.

• SEO earns a ranking in a list of ten blue links. The user scans the list and chooses.
• GEO earns a mention inside a written answer. There is no list. The model decides which sources to trust, quotes them, and moves on.

That difference changes the work. Ranking signals like backlinks still help, but what matters most for GEO is whether a model can read your content cleanly, trust it, and pull a clear, quotable answer out of it. A page built to rank is not automatically a page a model wants to cite.

What AI engines actually cite

Models reach for sources that are easy to parse and easy to trust. In practice that means a few things:

• Content that answers a specific question directly, in the first sentence, before any preamble.
• Clean structure and valid technical markup the model can read without guessing.
• Claims that are corroborated elsewhere, so the model has more than one reason to believe them.
• A clear sense of who you are as an entity, consistent across the places the model has seen you.

This is why a brand-new page on its own rarely gets cited. The model has no history with you yet. GEO is the work of building that history on purpose.

How a GEO program works

A real GEO engagement is a loop, not a one-time project, because the AI landscape never stops moving. At Origo it runs in four moves:

1. Measure. Run your brand against every major engine across the questions your buyers ask, and document exactly who gets cited and where the gaps are.
2. Fix the foundation. We produce the content, schema and llms.txt changes that let the models read, understand and trust your pages. You publish them.
3. Monitor and recommend. The engine checks the answers daily, flags what changes, and drafts the specific fixes that move citations.
4. Verify by hand. AI generates every recommendation; you decide what ships. We do not claim human review happens automatically. You are the check.

That last step is the part most tools skip. A model can hallucinate a citation as easily as anything else, so a number you cannot verify is not a result. Every answer is stored word for word so you can check it yourself, and every run after you publish shows whether the fix landed.

You cannot improve what you have not measured, and you cannot trust what you have not checked.

Done well, GEO turns the AI answer from a place you are absent into a place you are the source. That is the whole game.

Sources

• SparkToro, In 2026, less than one third of Google searches still send a click, June 2026
• OpenAI 900 million weekly users, via Search Engine Land, February 2026
• Perplexity 780 million monthly queries, via TechCrunch, June 2025