The GEO agency for B2B SaaS.

Traditional SEO optimises for position in a ranked list of results. A buyer scans the list, clicks, and judges your page. GEO works on a different moment. When a buyer asks an AI tool to recommend software, it returns one synthesised answer with a short list of vendors, and the buyer rarely sees the ten links underneath it. If your brand is not in that answer, you are not in the consideration set.

That changes what you optimise. You are no longer only competing for a position on a page. You are competing to be a source a model trusts and can quote. That depends on your own pages, but just as much on what other sites say about you, how consistently your company is described across the web, and whether your content answers the questions buyers actually ask.

It also changes how you measure. Rankings and clicks tell you little about whether ChatGPT recommends you. GEO is measured by visibility, share of voice and citation rate across the prompts that matter, broken down by engine. We explain the full method on our methodology page.

Generative engines build answers from a mix of sources. Some come from a live search index, some from what the model already learned during training, and some from pages the engine retrieves at the moment of the question. Across all of them, three things tend to decide whether a software company is named.

The first is the entity: whether the engine can tell exactly who you are, what category you belong to and who you serve. Inconsistent naming, outdated descriptions or a confused identity mean the engine either guesses or leaves you out. We cover the mechanics in our guide to entity authority.

The second is corroboration. Engines weigh what independent sources say about you, including review platforms, comparison lists, editorial coverage and community threads. A brand talked about across those sources is easier for a model to recommend with confidence than one that only describes itself.

The third is extractability. Content that opens with a direct answer, is specific about the product, and is structured so a passage can be lifted out cleanly is more likely to be quoted. That is why our content is answer-first and why we treat structure as a ranking factor in its own right. For the detail, read how Google AI Mode and AI Overviews select sources and how ChatGPT decides which brands to recommend.

A real GEO programme is a rhythm of work, not a one-off audit. Each month our team writes, edits and publishes answer-first content, rewrites existing pages based on content-gap findings, and ships new landing pages. Technical fixes are implemented directly on your site, including schema, metadata and internal linking, not just listed in a report and handed back.

Alongside that, we review off-site opportunities: the third-party websites and lists AI engines pull from in your category, and the gaps between you and your competitors. We prioritise targets and, where you want it, run the placement work through digital PR.

Measurement runs throughout. You get a live dashboard benchmarked against named competitors, regular review meetings and a dedicated Slack channel, with reporting on leads, pipeline and revenue next to the citation data. If a competitor overtakes you on a key prompt, we see it early and adjust the underlying work instead of waiting for the next report.

A GEO programme is only as credible as its measurement. We track a fixed prompt set across ChatGPT, Copilot, Claude, Gemini, Google AI Overviews, Google AI Mode and Perplexity, and report four things. Visibility is how often your brand appears. Share of voice is how you compare with named competitors. Citation rate is how often your own pages are cited. Mention position is where in the answer you appear.

Where AI traffic reaches your site, we tie it to leads and pipeline, so the report speaks to a board and not only to a marketing team. Semrush research found that AI search visitors convert at 4.4 times the rate of traditional organic visitors, which is why we track them as a channel in their own right. The data sits inside our ContextualJourney™ platform next to traditional traffic and conversion reporting, so you can see how the two channels move together. The full method, including the tools we use, is on the methodology page.

Almost every SEO agency now sells some version of GEO. The label tells you nothing, so test the work behind it. A specialist can show you how it chooses the prompts that matter commercially for your category, how often it re-tests them, and how it maps the sources that shape the answers. It can show a real report, with AI metrics as the headline and not a slide at the back.

Ask what happens once a gap is found. Tracking visibility is not the same as changing it, and a credible agency has a plan for content, third-party coverage and on-site changes. Ask for evidence of citation movement on a comparable account, and ask what it does when a programme does not move.

We have set out the full list of questions in our guide on how to evaluate a GEO agency for B2B SaaS, and a scorecard you can use on any shortlist.

We specialise in B2B SaaS and software brands, most often at Series A and B, where the buyer journey and the budget are specific to that stage. We see the most impact where buyers research vendors before they speak to sales, which is where AI answers shape the shortlist.

GEO is likely to matter less for brands that sell mainly through direct relationships, enterprise procurement or local search. It is also premature for pre-product companies, because third-party presence depends on a product in market with real users who generate reviews and coverage. If that is you, we will say so on the first call.

Buyers do not type keywords into an AI assistant. They ask long, specific, personal questions, and the model silently expands each one into many sub-queries, pulling passages from across a category before it writes a single answer. This is sometimes called query fan-out.

That makes AI search closer to a raffle than a ranking. You win by appearing across as many of those sub-queries as possible. A question such as which London community suits an exited founder of a VC-backed company looking to go again, but bigger, has no search volume you could look up, yet it is exactly how buyers now ask. It is why we map 150+ prompts across the funnel and not a handful of head terms.

6sense's 2025 buyer research found that 95% of winning vendors were already on the buyer's day-one shortlist. AI answers make that shortlist even tighter, because a model cites a handful of sources and names a handful of vendors, not ten blue links to scan.

If you are not in that first synthesised answer, you are often not in the deal. That is the commercial case for working on AI visibility before a buyer ever reaches your site.

Google, ChatGPT, Gemini and the other engines now reward broadly the same thing: the clearly structured, well-sourced, frequently cited answer. They do not return the same results, so we measure each engine separately, but we do not try to game any one of them.

We optimise for engine-agnostic citation-worthiness: direct answers, specific detail, consistent entity data and independent corroboration. That holds up when an engine changes how it works, which they all do.