Be the answer AI engines give.

They overlap and they are not the same. Traditional SEO optimises for a ranked list of ten results. Generative engine optimization and answer engine optimization optimise for being selected, summarised and cited, which depends on entity clarity, content structure and third-party sources as much as on your own pages. In practice we run them together: the research is shared, and a page that deserves to rank is usually one restructuring pass away from being quotable.

We run a fixed prompt set across ChatGPT, Perplexity, Google AI Overviews and Copilot every month and record whether you appear, in what position, with what sentiment, and which domains were cited in the answer. Individual answers vary between runs, so the trend across a stable prompt set is the number that matters. You get the raw answers as well as the summary, because a claim you cannot inspect is not evidence.

Changes to your own pages, schema and naming can show up within weeks, especially in engines that browse live. Changing the third-party sources an engine trusts takes longer — a corrected listicle or an earned comparison placement has to be recrawled and re-weighted — but it also lasts far longer. We report both tracks separately so progress is never one blended number.

We trace the claim to the page that caused it and work that source: a correction request, an updated data point, a better page of our own, or a replacement source the engine trusts more. Arguing with the model does nothing; changing its inputs does. Accuracy monitoring is part of the monthly report rather than an emergency service.

Strong SEO helps and does not guarantee citation. Pages that rank well often need restructuring before an engine will quote them, and plenty of brands with excellent organic visibility are absent from the answers entirely because the comparison content in their category was written by someone else. The good news is that the same authority makes the GEO work faster once the structure is fixed.

ChatGPT, Perplexity, Google AI Overviews and Microsoft Copilot as standard, and we add engines when a client’s buyers use them — Gemini, Claude and vertical assistants included. The prompt set is portable, so adding an engine is a measurement decision rather than a new project.

Some answers send a click and some do not, which is exactly why the metric is citation rather than sessions. With 58.5% of US searches already ending without a click (Semrush), being the source that gets quoted protects demand that would otherwise disappear from your analytics. We still report assisted traffic and branded search movement, because those are where the commercial effect usually shows first.

Yes, and we treat it as a moving target on purpose. Coverage went from 6.5% of queries in January 2025 to nearly 25% in July, then back under 16% by November (Search Engine Land). So we optimise the pages that already rank for answer-shaped structure and entity clarity — work that pays whether the layout expands or contracts — rather than chasing one surface.

One monthly number covering measurement, your own content and structure work, and the third-party source programme, scoped from the baseline audit. You get the prompt set, the monthly report with raw answers and cited domains, the content changes, and the placement log. Everything stays in your name, and there is no lock-in.

If you want early positioning, yes — deliberately and with clear eyes. We run ChatGPT Ads for clients who want to be present as the surface matures, and we report it as a land-grab bet rather than a proven performance channel. GEO is the organic half of the same shift, and most brands should get the organic side right first.

Named senior specialists — the people who run the measurement also write the content plan. One weekly working session, one written monthly review, and a shared channel in between. Where your team wants to own the content production, we brief and review it instead, and hand over the documentation so the capability stays with you.

A mix of dedicated AI-visibility platforms and our own prompt runner, plus the classic search stack for the overlap. The tools matter less than the method: a stable prompt set, the same models and settings each month, and the raw responses stored so a trend can be audited rather than trusted. Generative systems vary run to run, so a strategy built on one screenshot is not a strategy. We record which citations each engine returned, how the language models described your website, and what changed since the previous month.

Less keyword work, more structure and facts. In practice a typical month includes rewriting a handful of pages into self-contained answers, tightening entity and naming consistency, adding or correcting data points that generative engines quote, chasing two or three third-party sources, and re-running the prompt set. It looks more like digital PR and content engineering than traditional search engine optimization, and it shares its research with the SEO plan so nothing is done twice. Where demand needs creating rather than capturing, paid social and paid search carry that load, and verticals with heavy comparison content — for instance eCommerce — usually see the fastest citation movement.