White Ocean Media
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    AI Visibility

    Get cited by ChatGPT, Perplexity and Google AI Overviews

    AI visibility, also called generative engine optimisation (GEO) or answer engine optimisation (AEO), is the practice of making a brand something AI systems can find, verify and choose to cite. Most agencies selling it treat it as on-page SEO: better headings, a tidier FAQ block, an llms.txt file. That helps, but large language models weigh a brand by what independent, reputable sources say about it, which is the same signal that has always driven PR. We build both ends: the structured, citable content AI systems can parse, and the earned media coverage that gives them a reason to trust what they find. It shows clearly in crypto and Web3 PR, where AI systems already lean on a small set of trusted outlets.

    Why does earned media affect what AI says about a brand?

    Generative engines don't take a brand's word for its own credibility. They cross-reference: is this company mentioned by outlets the model already trusts, in a context that corroborates the claim? A founder profile in a recognised trade publication, a quoted expert comment, a piece of press coverage picked up by multiple outlets: these are exactly the kind of independent, corroborating signals that give an AI system a reason to repeat a claim rather than hedge or omit it.

    This is the gap between an SEO agency bolting a GEO service onto its existing on-page checklist, and a PR agency that already knows how to earn third-party coverage, applying that skill to a new distribution channel. On-page structure decides whether a page can be extracted. Earned coverage decides whether the extraction is believed.

    What does an AI visibility engagement actually involve?

    Three layers, run together rather than sequentially. First, an audit of how a brand appears, or fails to, across ChatGPT, Perplexity, Gemini and Google AI Overviews for the questions its buyers actually ask. Second, structural work on its own site and public profiles: clear claims, defined entities, a genuine FAQ, consistent facts, an llms.txt file, so an AI system can extract and verify without guesswork. Third, the part most GEO offerings skip: earned media in the outlets, forums and reference sources large language models already draw on.

    How is this different from traditional SEO?

    Traditional SEO optimises for a ranked list of links a person clicks through. AI visibility optimises for being the fact an AI system states, or the source it names, inside an answer the person never has to click past. The mechanics overlap: both reward clear structure and real authority. But the endpoint is different, and so is the measurement: rankings and clicks give way to citation frequency and share of voice inside AI-generated answers.

    PROCESS

    How it works

    Our process

    01

    Audit

    Run the brand's actual buyer questions through ChatGPT, Perplexity, Gemini and Google AI Overviews. Record what's cited, what's missing, and who the AI trusts instead.

    02

    Structure

    Fix the on-page and entity-level gaps that stop an AI system from extracting and verifying the brand's own claims, including an llms.txt file and consistent facts across every public profile.

    03

    Earn

    Run the media relations and thought-leadership programme that gives AI systems independent, corroborating sources to cite. It's the same discipline behind every other service on this site, aimed at a new distribution channel.

    04

    Track

    Re-run the same prompt set on a fixed schedule and log whether citation, mention and sentiment are moving in the right direction.

    FAQ

    Common questions

    In practice, they describe the same discipline from two angles. Generative engine optimisation (GEO) is the broader term, covering visibility across conversational AI systems like ChatGPT, Perplexity and Gemini. Answer engine optimisation (AEO) is often used specifically for winning direct-answer surfaces such as Google AI Overviews and featured snippets. The underlying work is the same either way: clear structure, verifiable claims, real third-party corroboration.

    No, and any agency that promises this is overstating what anyone controls. Large language models decide what to cite based on training data, retrieval behaviour and model-specific weighting that no outside party can fully dictate or reverse-engineer. What a properly run programme can do is remove every avoidable obstacle: unclear structure, inconsistent facts, absent third-party corroboration. And it can consistently put a brand in front of the sources these systems already draw on.

    It helps but isn't required. AI systems draw on a wider set of sources than a page-one Google ranking implies, including forums, trade press, and reference sources that never compete for classic search rankings. A brand with strong earned media and clean structure can be well cited by AI systems while still building its conventional SEO position.

    By running a fixed set of real buyer questions across ChatGPT, Perplexity, Gemini and Claude on a consistent schedule, and logging whether the brand is mentioned, whether it's cited as a source, and how it's framed relative to competitors. It's a monitoring discipline, not a one-off audit. AI answers change as models update and as new coverage lands.

    No, it depends on both. The earned-media work is traditional PR, aimed at a channel that now matters as much as a journalist's inbox or a Google results page. The on-page structural work overlaps heavily with technical SEO. AI visibility is best understood as an additional lens on work most brands are already doing, not a replacement for it.
    DISCOVERY

    Build the authority that AI can see

    Tell us about your brand and your goals. We reply within 24 hours.

    business@womedia.co