The prompt panel
Two hundred commercial prompts written from your buyers' language, not your product vocabulary. Documented and handed over, so you can re-run it yourself or hold us to it.
A GEO baseline audit measures whether generative engines mention, cite or ignore your brand. We run a fixed panel of your buyers' commercial prompts across ChatGPT, Perplexity, Gemini, Copilot and Google AI Overviews, then record where you appear and who appears instead. You get the number you are starting from.
Typically a fixed-scope one-off, delivered in 12 working days.
A GEO audit measures four things: whether an engine names you, whether it links you, which sources it pulled from, and who it recommends when it does not recommend you. Those four together give a share-of-voice figure you can track, rather than an impression of how things are going.
There is no rank tracker for generative engines. Ask ChatGPT the same question twice and the wording changes; ask it from a different account and the sources can change too. That variability is exactly why most agencies avoid measuring this and sell you activity instead of a number.
The way around it is sampling. Run enough prompts, enough times, across enough engines, and the noise averages out into something stable enough to trend. A single answer is an anecdote. Two hundred prompts run weekly is a measurement.
So the audit is not a screenshot of ChatGPT saying something nice about you. It is a panel: a fixed, written-down set of the questions your buyers actually type, executed cold with no personalisation, scored the same way every time. Fixed matters more than large — a panel you change halfway through cannot show a trend.
The uncomfortable half of the output is the competitor half. When an engine answers a buying question and does not name you, it names somebody. Knowing who, and which of their pages the model pulled from, is usually the most actionable page of the whole report.
You receive the prompt panel itself, a scored visibility baseline per engine, a source analysis showing which pages models retrieved, a competitor share-of-voice table, and a prioritised list of the gaps worth closing first. The panel is yours to keep and re-run.
Two hundred commercial prompts written from your buyers' language, not your product vocabulary. Documented and handed over, so you can re-run it yourself or hold us to it.
Mentioned, cited with a link, or absent — scored separately for ChatGPT, Perplexity, Gemini, Copilot and Google AI Overviews. They disagree more than you would expect, and the differences are instructive.
Which URLs the models actually retrieved when answering. Frequently these are third-party listicles and forum threads rather than anyone's product pages, which changes where you should spend.
Who gets named when you do not, how often, and on which prompts. This is the section clients circulate internally.
The prompts where you are closest to breaking through, separated from the ones you will not win this year. Effort against plausible return, ordered.
Written scoring rules so a re-run six months from now is comparable to this one. Without it you have a snapshot, not a baseline.
The audit runs over twelve working days: prompt design with your sales team, a cold run across five engines, source and competitor analysis, then a live readout. Your time is roughly two hours, most of it spent telling us how buyers actually phrase things.
We sit with whoever talks to your buyers and collect the questions they genuinely ask. Sales calls are a better source than your keyword tool here, because generative queries are conversational and long.
→ A written 200-prompt panel, approved by you
Every prompt executed without personalisation, logged in / logged out, across ChatGPT, Perplexity, Gemini, Copilot and AI Overviews. Cold matters — a logged-in run reflects your own history, not a buyer's.
→ Raw responses captured and scored
For every answer, what was cited and who was named. We cluster the sources to show which kinds of pages the models trust for your category, and which of your competitors have quietly become the default answer.
→ Source clusters and a share-of-voice table
A live walkthrough with your team, then a prioritised gap list. If the honest answer is that your constraint is classic SEO or content depth rather than GEO, we say so and point you there instead.
→ Board-ready readout and an ordered gap list
An SEO audit asks whether a search engine can crawl and rank your pages. A GEO audit asks whether a language model retrieves and repeats them. The inputs overlap — both need crawlable, well-structured content — but the measurement, the competitor set and the winning content shape are different.
| SEO audit | GEO audit | |
|---|---|---|
| Question answered | Can engines crawl, render and rank this site | Do models retrieve, cite and repeat this brand |
| Measurement | Rankings and impressions from Search Console | Share of voice across a fixed prompt panel |
| Unit of analysis | The page | The passage, and the third-party source that mentions you |
| Competitor set | Whoever ranks for your keywords | Whoever the model names — often not the same companies |
| Typical fix | Architecture, internal linking, page depth | Answer-shaped content, entity signals, third-party presence |
| Feedback speed | Weeks, via a rank tracker | Weekly, via a re-run of the panel |
You need a GEO baseline when AI referral traffic appears in analytics, when sales hear buyers quoting an assistant, when a competitor keeps getting named in answers, or simply when nobody in your business can say whether models mention you at all.
Most brands start lower than they expect. Engines lean on third-party sources — comparison posts, forums, review sites — far more than on your own pages, so companies with strong classic SEO are often close to invisible in generative answers until that gap is closed.
Each answer is written to stand alone in 40 to 60 words — the shape an AI Overview or Perplexity citation lifts. Ships with FAQPage schema.
An SEO audit asks whether search engines can crawl and rank your pages. A GEO audit asks whether language models retrieve and repeat your brand when a buyer asks a question. Both need sound technical foundations, but the measurement and the winning content shape differ substantially.
Yes, through sampling. Any single answer is unreliable, so we run a fixed panel of two hundred prompts across five engines and score the aggregate. The individual responses vary; the share-of-voice figure across the whole panel is stable enough to trend week over week.
Two hundred commercial prompts as standard, written from your buyers' actual language rather than your product vocabulary. Larger panels are available for broad catalogues. What matters more than size is that the panel stays fixed, otherwise later runs are not comparable.
ChatGPT, Perplexity, Gemini, Microsoft Copilot and Google AI Overviews as standard. They disagree with each other more than most people expect, which is itself useful — being strong in one and absent from another usually points at a specific, fixable source gap.
You get a prioritised gap list and you are free to action it yourself; the panel and methodology are handed over. Clients who continue with us move to an ongoing programme with weekly panel re-runs, but the audit is deliberately sold as a standalone diagnostic.
Usually yes, because the absence is the finding. Citation work is slow — it depends on third-party mentions accumulating — so a brand with zero presence today benefits most from starting to measure now, before a competitor becomes the entrenched default answer.
Thirty minutes with a senior strategist. We pull your live visibility while we talk and tell you plainly whether a GEO audit is what you need — or whether your problem sits somewhere else.