How Do You Do GEO (Generative Engine Optimization)?

GEO means optimizing your content so AI answer engines – ChatGPT, Perplexity, Google AI Overviews, and others – cite and recommend your brand when users ask questions in your category. You do it by publishing clear, structured, factual, quotable content that directly answers real questions, backing claims with evidence, and earning the third-party mentions these models trust.

Detailed Answer

Generative engine optimization is the practice of getting your brand surfaced inside AI-generated answers rather than just inside a list of blue links. As more people ask an AI assistant instead of running a search and clicking, the question shifts from 'do we rank' to 'does the model mention us when it answers.' GEO overlaps with SEO but optimizes for a different consumer: a model that reads, synthesizes, and cites rather than a person who scans and clicks.

Answer real questions directly and completely. Models pull from content that answers a question cleanly, so structure pages around the actual questions buyers ask and put the answer up front – a direct two-sentence response, then the detail. Use clear headings phrased as questions, short scannable paragraphs, and explicit definitions. The content that gets quoted is the content that makes the answer easy to lift. Burying the answer under throat-clearing intros is the fastest way to get skipped.

Be quotable, specific, and factual. AI engines favor content with concrete facts, numbers, definitions, and statements they can cite with confidence. Vague [marketing](/services/marketing/) copy gets ignored because there is nothing to quote. Make claims specific, attribute data to sources, keep facts current, and write in plain declarative sentences a model can extract without distortion. Structured formats – clear lists, tables, FAQ blocks, and definitions – are disproportionately easy for these systems to parse and reuse.

Build authority and third-party citations. Models weight sources they consider trustworthy, and trust is partly earned off your own site. Mentions in reputable publications, directories, comparison pages, expert roundups, and credible communities all feed the picture these engines build of who is authoritative in your category. This is where GEO meets a real [growth strategy](/services/strategy/): you are not just publishing pages, you are building the external footprint that makes a model confident enough to name you. A site with no outside corroboration rarely gets cited even if its own content is good.

Add machine-readable structure and measure mentions. Schema markup, FAQ structured data, clean metadata, and consistent entity information help engines understand what your content is and how to use it. On the measurement side, GEO needs its own scoreboard: instead of only tracking rankings and clicks, track whether and how AI engines mention you – run representative prompts across the major assistants, log when your brand appears, in what context, and against which competitors, and watch that share over time. That gives [measurement](/services/measurement/) you can actually act on rather than guessing whether the work landed.

GEO is not a separate empire from SEO – it is the next layer on the same foundation of clear, authoritative, well-structured content, tuned for a reader that is now a model. If your category is one where buyers are starting to ask an AI assistant instead of running a search, and you have no idea whether you get mentioned, we should talk.

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Frequently asked questions

How is GEO different from traditional SEO?

SEO optimizes to rank in a list of links that a person clicks; GEO optimizes to be cited inside an AI-generated answer the person reads directly. They share a foundation – clear, authoritative, well-structured content – but GEO cares more about being quotable, factual, and corroborated by trusted third parties. The measurement also differs: SEO tracks rankings and clicks, while GEO tracks whether AI engines mention you. In practice you build on your SEO work rather than replacing it.

Which AI engines should GEO target?

The main ones today are ChatGPT, Google AI Overviews, Perplexity, and the assistants built into other large platforms, with the list shifting as the market moves. You do not optimize for each one separately so much as optimize for the shared behavior: pulling from clear, factual, well-structured, authoritative content. Start by checking which engines your buyers actually use to research your category. Then run representative prompts across those engines to see where you already appear and where you do not.

How do you measure whether GEO is working?

Build a scoreboard of AI mentions rather than relying only on rankings. Run a set of representative prompts a real buyer would ask across the major assistants, and log when your brand appears, in what context, and against which competitors. Track that share of mentions over time as you publish and earn citations. Rising mention share in the prompts that matter is the signal that the work is landing.

Does GEO require new content or can I use what I have?

You can often start with what you have, but it usually needs restructuring. Existing pages may have the right information buried under vague intros and unclear formatting that models struggle to extract. The fastest wins come from rewriting key pages to answer real questions directly, adding factual specificity, and applying structured formats like FAQ blocks and schema. New content then targets the question-shaped gaps your current pages do not cover.