Get cited inside the answer, not lost beneath it.

Generative engines do not crawl the web live in the way a search index does. Many rely on a mix of training data, retrieval from indexed sources and, increasingly, real time browsing. What they consistently favour is content that is unambiguous, factually checkable and repeated consistently across independent sources, rather than content that is merely well optimised for a search results page.

This shifts the work in a specific direction. Vague marketing language gets summarised or dropped. Specific claims, numbers, named processes and clearly attributed facts get quoted, because a model generating an answer is trying to reduce its own risk of being wrong, and specific, sourced statements are lower risk to repeat.

We also look at consistency across the web, not just your own site. If your pricing, positioning or service descriptions contradict themselves across your site, directories, press coverage and social profiles, a generative engine has less reason to trust any single version. Cleaning that up is often the highest leverage early step.

The pages that get cited by generative engines tend to share a shape: a clear statement of what the business does, specific numbers where they exist, named methodologies rather than vague claims of expertise, and dates that show the information is current. We rebuild your highest value pages around this shape without losing the persuasive writing that still needs to convert an actual human reader.

Original data is particularly valuable here. A generative engine has no incentive to quote a paraphrase of something ten other sites already say. It has every incentive to quote the one source with a number, a study or a specific example nobody else has published. Where clients can share genuine data, case results or original research, we prioritise turning that into citable content ahead of general commentary.

We also build content that directly answers comparison and recommendation style prompts, since a large share of commercially relevant AI queries are effectively "recommend me a provider for X". Being the clearest, most specific answer to that exact framing matters more than ranking well for the equivalent typed search.

Measurement here is younger than traditional analytics and we are honest about that. We track brand mentions and citations across major AI tools through a mix of manual prompt testing and emerging monitoring tools, watch for referral traffic tagged from AI platforms in analytics, and track branded search lift as a proxy signal when a business starts being recommended more often.

This is not as precise as a keyword ranking report, and we would rather tell you that plainly than dress up a rough number as certainty. What we can show reliably is whether your business appears when we run a consistent set of test prompts month over month, and whether that presence is improving.

GEO makes the most sense for businesses in categories where people genuinely ask AI tools for recommendations or comparisons, B2B services with a considered buying process, and businesses with real expertise or original data worth surfacing. It compounds well alongside SEO and AEO rather than replacing either.

It is a weaker starting point for businesses with no informational content at all, since generative engines have nothing consistent to draw from yet, and for extremely local, low consideration purchases where AI recommendation behaviour is still limited. In those cases we usually suggest building the SEO and content foundation first.