Generative Engine Optimization
Turning AI into a channel that sends you readers
“We used to optimise for a search engine to rank. Now we optimise for an answer engine to understand.”
01 — What is GEO
What is GEO?
GEO — Generative Engine Optimization is the practice of structuring content so it shows up, and gets cited, in what generative engines (ChatGPT, Perplexity, Gemini) actually say.
To be the cited source inside an AI answer, and the one it recommends.
SEO targets keyword rankings. GEO targets how a model understands meaning and relates entities.
02 — Why GEO matters
Why it matters now
Search habits changed
More people ask a question outright than type keywords.
Better-qualified traffic
Someone asking a specific question is usually closer to a decision.
Authority, demonstrated
When an AI quotes your position as the answer, that is the claim being made for you.
Reusable by construction
Content structured well for models turns out to be good social material too.
03 — GEO vs SEO
GEO against SEO, side by side
| Dimension | SEO | GEO |
|---|---|---|
| Goal | Rank | Be the answer |
| Audience | Google's algorithm | Large language models |
| Method | Keywords, backlinks | Structured data, semantic relationships |
| Output | A list of blue links | An answer, with citations |
04 — Princeton GEO research
Nine methods, measured: the Princeton study
A paper from Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi, "Generative Engine Optimization", tested nine concrete tactics and measured how much each raised the odds of being cited by engines such as ChatGPT and Perplexity:
| Method | Visibility gain | What it means in practice |
|---|---|---|
| Cite authoritative sources | +40% | Add credible outbound links and references so a claim has third-party backing. |
| Use concrete numbers | +37% | Replace vague wording with percentages, counts and measured quantities. |
| Quote named experts | +30% | Direct quotations from people in the field, attributed by name. |
| Write with authority | +25% | A confident, objective register — the way someone who knows the field writes. |
| Say it plainly | +20% | Restate hard ideas in clear, well-structured language so less is inferred. |
| Use the field's terms | +18% | The accepted technical vocabulary, used precisely — those words are the entities a model matches on. |
| Vary the wording | +15% | A wider vocabulary and varied sentence shapes help a model pick out what matters. |
| Read well | +15% ~ +30% | Coherent structure and flow — the same properties a model is predicting against. |
| Keyword stuffing | -10% | (Avoid.) Deliberate repetition reads as content-farm output and lowers your citation rate. |
“AI search is a contest over credibility and entity relationships. A model does not invent a brand that is not there — it cites what is well-backed, well-evidenced and clearly structured.”
— TauX engineering
05 — How GEO works
How we run a GEO engagement
Step 1. Build the answer container
Not a website so much as a library laid out for machines.
- Clean Schema.org markup
- Question-and-answer content structure
- Fast enough that nothing times out
Step 2. Fill it with something worth citing
Models reward a distinct position and discard filler.
- Answers to problems people actually have
- Expert judgement with evidence attached
- Kept current, with the dates to show it
Step 3. Build the trust graph
Get authoritative sources standing behind your answer.
- Relevant outbound links
- Social signals and brand mentions
Ready to start?
GEO compounds. Starting now means being the cited source while your competitors are still arguing about whether this matters.
Read it and would rather not do it yourself? We can do it for you.