---
title: "GEO Guide: how to get AI to cite you | TauX"
description: "What Generative Engine Optimization is, how it differs from SEO, and the nine methods a peer-reviewed study found actually move citation rates."
url: "https://taux.io/en-US/geo-guide"
locale: "en-US"
alternates:
  ja-JP: "https://taux.io/ja-JP/geo-guide"
  ko-KR: "https://taux.io/ko-KR/geo-guide"
  zh-Hans-CN: "https://taux.io/zh-Hans-CN/geo-guide"
  zh-Hant-TW: "https://taux.io/zh-Hant-TW/geo-guide"
---

# 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. 

**The goal**

To be the cited source inside an AI answer, and the one it recommends.

**The difference**

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               |

**SEO Goal** Competing for the click 

**GEO Goal** Competing for the citation 

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.

[See the GEO service and pricing](https://taux.io/en-US/geo-optimization) [Book a GEO consultation](mailto:hello@taux.io) 

Read it and would rather not do it yourself? [We can do it for you](https://taux.io/en-US/geo-optimization).