What is GEO? A founder's guide to generative engine optimization

Generative engine optimization (GEO) is the practice of influencing how generative AI systems answer questions about your category, your competitors, and your brand. If your customers are asking ChatGPT, Perplexity, Gemini, or Google AI Overviews instead of typing into a search bar, GEO is how you stay in the conversation.

Why GEO is different from SEO

Classic SEO optimizes for a list of links. GEO optimizes for a synthesized answer. Search engines reward authoritative pages on your own domain. AI engines reward authoritative mentions across the web that they can cite as sources.

The shift sounds subtle, but it changes which moves matter. Building a thousand backlinks to a thin landing page no longer pays off. What pays off is showing up, in context, on the handful of websites the model trusts when it composes its answer.

How AI engines pick what to cite

Each engine has its own retrieval and grounding stack, but the common signals are remarkably consistent:

• Editorial sources with a track record on the topic.
• Pages that are clearly structured and easy to extract from.
• Mentions that include specific, factual statements.
• Recency and freshness for time-sensitive topics.

The GEO playbook

A workable GEO program has three parts: build off-site mentions on the websites your target engines actually cite, structure your own site so it can be quoted accurately, and measure citation share over time so you know what is working.

1. Map the citation graph

Start by querying the engines for your most valuable prompts and recording which domains they cite. The shape of that list, not your gut, decides where to invest.

2. Earn placements that are quotable

A placement is only useful if a model can pull a clean fact out of it. Aim for paragraphs that pair your brand with a specific claim, number, or capability.

3. Track citations, not rankings

Rankings still matter for traditional search, but the new metric is citation share: out of all the answers in your category, how often does your brand appear, and where in the answer.

Where Outreach Monkey fits

Outreach Monkey is built for the off-site half of this playbook. We identify the websites that AI engines cite for your category, run outreach campaigns to land mentions on those sites, and report citation share over time so you can see your brand entering the model’s answer.