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What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the work of making sure your brand, products and content are named, and described accurately, in AI-generated answers on assistants like ChatGPT, Perplexity, Google AI Overviews, Claude and Gemini.

Traditional SEO

Someone searches: "best running shoes"

→ A page of results

→ They click one

→ You compete for that click

GEO (AI answers)

Someone asks: "What are the best running shoes for marathon training?"

→ The assistant writes an answer

→ It names a few brands, often with reasons

→ You want to be in that answer

SEO = compete for a click. GEO = compete for a mention.

An Example

These two illustrations use made-up brands and sources. They are not real answers, but they show the difference between being named and being left out.

Prompt: "What are the best sustainable running shoes?"

Illustrative answer:

For sustainable running shoes, here are some options:

1. Example Brand Trail Runner: made with recycled materials. [site-one.com]

2. Competitor A Road Racer: lightweight and bio-based. [site-two.com]

Example Brand is named. The answer cites site-one.com as a source. If Example Brand were not covered on pages like that one, it might not appear here.

Prompt: "Which running shoe brands are growing fastest?"

Illustrative answer:

Brands often named as growing quickly include:

1. Competitor A, with growth reported by [site-three.com]

2. Competitor B, with growth reported by [site-four.com]

Example Brand is not named

Example Brand is left out of this answer, even though it was named in the first. A2ZReach calls this an exclusion: a tracked prompt where an AI assistant named your competitors but not you. The next step is to find which sources the answer relied on and why they do not cover you. See Exclusion Analysis.

How AI Assistants Build Answers

🔍

Query

User asks

→

📚

Retrieve

Pull sources

→

🧠

Synthesize

Build answer

→

📎

Cite

Link sources

→

💬

Respond

User sees

Our reading: GEO work is mostly about steps 2 to 4. Be easy to retrieve, worth citing and worth including.

Why GEO Matters Now

  • People use AI to research. A Pew Research Center survey of 5,119 U.S. adults (February 2026) found that about 49% use AI chatbots, up from 33% in 2024, though Pew notes the two questions were not identical. It also found that 42% use chatbots to search for information.
  • ChatGPT is large. OpenAI reports 1.2 billion weekly ChatGPT users as of September 29, 2026 (OpenAI).
  • Answers can replace the click. In a Pew study of 900 U.S. adults' Google browsing in March 2025, people clicked a traditional result link on 8% of visits that showed an AI summary, against 15% of visits without one. The study covers Google only.

If you are not measuring how often AI assistants name your brand, you do not know how much of that research reaches you.

What GEO Work Measures

A2ZReach asks AI assistants the prompts your buyers are likely to ask and saves each full answer with the sources it cited. From those answers it reports:

  • Visibility Score: how often your brand appears in answers to prompts that do not name it
  • Share of Voice: your mentions as a share of all the brand mentions in those answers
  • Average Position: where you are named when you are named
  • Exclusions: the prompts where competitors were named and you were not, with the sources the answer cited
  • Citations: which sites and pages the answers lean on

See Visibility Tracking for how the first three are counted, and the Metrics Glossary for the rest.

GEO vs AEO: Same Thing, Different Name

You will see both terms used: GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization). They refer to the same practice. GEO emphasizes the generative nature of the assistants. AEO emphasizes the answer format. We use GEO as the primary term.