Helping you retain visibility in the world of generative AI

LLM optimisation is the work of making your brand and content more likely to be found, understood and cited by large language models: the systems behind ChatGPT, Perplexity, Copilot and Google’s AI Overviews and AI Mode. In practice it means making your content technically reachable, structuring it so machines can extract answers cleanly, and building the authority signals that make you a source worth citing. The end goal is brand visibility inside AI-generated answers, including the growing share of searches that never produce a click.

The foundations are the same: crawlable content, genuine authority, helpful pages. The differences sit in the goal and a few of the tactics. Traditional SEO optimises for rankings and clicks; LLM optimisation optimises for being cited within an answer, which puts more weight on extractable formats, natural conversational language, and understanding how LLMs source information through query fan-out. In our experience the technical output overlaps heavily, which is why the same work usually benefits both.

Broadly, yes. GEO (generative engine optimisation) and AEO (answer engine optimisation) are labels the industry uses for the same discipline; we call it LLM optimisation. Whatever the label, the substance is standard search foundations applied to how LLMs retrieve and present information. Be cautious of any pitch that frames GEO as a separate discipline with its own guaranteed tactics, because Google’s own guidance is clear that optimising for generative AI search is still SEO.

Google’s AI Mode and AI Overviews, ChatGPT, Copilot and Perplexity are the platforms we test against most, because they carry the bulk of AI search behaviour among our clients’ audiences. The good news is that the work isn’t platform-specific: extractable, authoritative, crawlable content improves your standing across all of them, so you’re not rebuilding your strategy every time a new platform gains share.

No, and we’d encourage you to be wary of anyone who says they can. Nobody outside the platform controls what an LLM cites; the systems are probabilistic and they change frequently. What we can influence is the set of inputs that genuinely affect your likelihood of being cited: whether crawlers can reach your content, whether it’s structured for extraction, whether your authority signals are real, and whether your content is current. We then measure honestly against a baseline, so you can see what moved rather than taking our word for it.

Through structured prompt testing. We agree a set of prompts that reflect how your buyers actually ask, run them across the AI platforms, and record whether you’re cited, how often, in what context, and how that compares with competitors. That baseline is taken before any work starts, and the same prompts are re-run as the engagement progresses. Results are reported through our AI Analysis Dashboard alongside your organic search data, so AI visibility sits in one view with the rest of your performance.

No. LLM optimisation builds on SEO foundations, and it works precisely because those foundations are in place: a site that isn’t crawlable or authoritative won’t be visible to LLMs either. Google still drives the large majority of search traffic, and its AI features are rooted in the same ranking and quality systems as classic search. We treat LLM optimisation as an extension of a strong SEO programme, which is why it pairs naturally with our monthly SEO management retainers.