Generative engine optimisation (GEO): a guide

Generative engine optimisation, or GEO, is work intended to improve how a product or page appears in generated answers. For a software company, that might mean being named in a recommendation, having a capability described correctly, or providing a source the answer cites.

The useful starting point is a question customers ask before choosing a product. Save the answer and its sources, inspect what is missing or incorrect, and decide whether you can contribute something useful. This guide explains that process for a small team.

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What generative engine optimisation actually is

Start with how the engine produces an answer, because the tactics fall out of the mechanism. When you ask a generative engine a question like "what is the best tool for X", one of two things happens, and increasingly both happen at once.

When an answer uses live retrieval, the system searches for information and may return source links with its response. Those links are inspectable evidence; they do not necessarily expose every page used along the way.

The second is parametric recall. The model has already read a large slice of the public web during training. Some facts about your product, or your category, or your competitors, are baked into its weights. When the engine answers from memory rather than from a live fetch, the question becomes whether the model learned anything about you at all, and whether what it learned was accurate.

You can inspect public pages and returned sources, but you cannot directly edit a model’s training material. Focus the work on information you can verify and maintain, then measure how answers change.

Why GEO is not SEO

The work overlaps because useful, accessible pages can serve readers coming from either route. Measure search performance and generated answers separately so one result is not mistaken for evidence about the other.

The unit of success changed

A citation points to a source, which may be your homepage, documentation or an article. Make the relevant claim easy to find and verify. A product capability, limitation or worked example gives a reader more to assess than a broad adjective.

You can win without the click

A generated answer can introduce a product without producing a visit. That is an additional observation to record, but its value is hard to establish from a mention alone. Customer conversations and referral outcomes can help explain the wider effect.

The corpus is wider than your site

Your own pages and pages published by others can both appear in answers. Review them together. Documentation may establish a capability, while a customer review or technical comparison may explain how it performs in practice.

The GEO playbook, in priority order

Begin with a problem you can observe. If the answer describes an old price, correct the source. If customers repeatedly ask a question that your site never answers, plan a useful page for it.

Make claims an engine can lift

Review the product’s core pages for claims that need explanation. “Powerful analytics” tells a reader little. An account of which events can be tracked, how setup works and what the report shows gives them a basis for comparison.

Practically, this means writing declarative, specific, self-contained sentences. State what your product does, who it is for, how it differs from the obvious alternative, and what it costs, in plain language, near the top of the relevant page. Each sentence should make sense if an engine quotes it on its own, with no surrounding context. Imagine the model has a pair of scissors and can keep only one sentence. Write that sentence.

A concrete test: take any paragraph on your site and ask whether it answers a question a user would actually type. If a paragraph answers "what does this do for a team of five" or "how is this different from the market leader", it is GEO-ready. If it only signals vibe, rewrite it.

Be a clear, consistent entity

Engines reason about the world in terms of entities: named things with stable properties. Your product is an entity. So is your company, your category, and each competitor. The engine's job, when it answers, is to retrieve or recall the right entities and describe them correctly. Your job is to make your entity easy to identify and hard to confuse.

That means using your product name consistently across every surface, pairing it with the same short category descriptor every time, and making sure the obvious external references agree. If your homepage calls you a "customer feedback platform", your directory listings, your company profiles, your social bios, and your documentation should not call you four other things. Consistency is what lets a model collapse all those mentions into one confident entity rather than a fuzzy cloud it hedges on.

Ask a few assistants to describe the product and inspect their answers. An error identifies something to investigate, but it does not always identify the source. Check returned links before deciding which page needs a correction.

Add structured data

Structured data is machine-readable markup you add to your pages that states facts explicitly rather than leaving them buried in prose. Schema.org markup for your organisation, your product, your FAQ entries, and your pricing gives a retrieving engine an unambiguous version of the facts it would otherwise have to infer from your layout.

Choose markup that matches the visible page, validate it and maintain it when the product changes. Google says its AI search features do not require special structured data. Visible, useful answers matter independently of whether a rich result displays them.

Answer the real questions in full

Use customer questions to identify gaps in the site. A setup question may belong in documentation; a switching question may need a comparison; a question about cost may need a clearer pricing explanation. Give each the space its answer requires.

State the answer early, then explain its limits and evidence. For a comparison, include where each option fits and where it does not. The page should let a reader make a choice without discovering an omitted constraint later.

Earn mentions in the sources engines read

Review the sources returned on the questions you care about. If a relevant comparison has outdated information, request a correction with evidence. If a community discussion needs an answer you can provide, contribute it with your affiliation disclosed.

For a solo founder the realistic version of this is unglamorous and works. Be genuinely useful in the communities where your users already discuss the problem, so that the threads an engine retrieves happen to mention you in context. Get listed in the directories and review sites for your category, accurately described. Earn the comparison-article mentions by being a real option worth comparing. None of this is link-buying or spam. It is being a known, correctly-described option in the places that already shape what the engines believe.

Do not fabricate reviews or pose as an independent customer. Readers need to know whose experience a statement represents, and promotional participation must follow the platform’s rules.

Measuring whether GEO works

GEO is harder to measure than SEO because the win is often invisible. There is no ranking position for "named in a ChatGPT answer". You have to assemble the picture from a few angles.

Ask the engines your category's real questions, on a regular cadence, and record whether you are mentioned and how accurately. That is your direct signal. Watch referral traffic from the AI assistants in your analytics, which is small for most products today but worth a trend line. Keep an eye on Search Console for the question-shaped queries you are now answering, since the same content earns both retrieval into AI answers and traditional impressions. None of these is a single clean number. Together they tell you whether the engines are starting to know you.

Use repeated checks to look for patterns. Keep the question set and measurement surface stable, and log changes to your own pages so you can investigate whether an answer used the revised material.

Where to start

If you do nothing else, do the first two steps. Rewrite your core pages so they contain claims an engine can lift, and make your product a clear, consistently-described entity across every surface. Those two are cheap, they sit entirely within a solo founder's control, and they are the foundation everything else builds on. Structured data, question pages, and earned mentions all compound on top of a clear entity making liftable claims. They do little on top of vague positioning.

When choosing between tasks, prefer a correction or resource whose value you can explain to a customer. That gives you a useful outcome even when the next AI answer does not change.

The free scan provides an initial view of your product’s discoverability. AfterLaunch then monitors those areas and prepares growth work with evidence and a draft for review. You can also run the checks above manually with a small, stable question set.