{Generative engine optimization}

Being one of the companies named when a buyer asks an AI assistant who to consider in your category.

Your buyers are researching in ChatGPT, Perplexity, AI Overviews, Claude, and Gemini before they ever reach a search results page. This is the work of showing up in those answers.

Why it matters

Buyers are asking before they search.

Someone evaluating vendors opens an assistant and asks who they should be looking at. They get three or four company names and a sentence about each. Being one of those names carries the weight of a recommendation — it arrives as an answer from a tool they already use daily and trust.

Assistants don't rank pages. They assemble answers from sources they trust: media coverage, comparison lists, structured pages, and content that says something the model can't get anywhere else. That's a different job than ranking, and it needs different work.

What we see go wrong

What we see go wrong.

It's treated as the same job as rankingThe two are related — pages that rank well are often the ones models draw from. But being named in an answer is a second outcome, and it takes work that ranking alone doesn't cover.
The content restates what everyone already saysModels synthesize the consensus by default. Content that repeats it gives them nothing new to cite.
Nothing outside the site backs it upAssistants weigh what others say about a company more heavily than what the company says about itself. A site with no media coverage is a claim with no corroboration.
Nobody has actually checkedMost companies have never run the prompts their buyers use. You can't fix invisibility you haven't measured.

What we do

What the work looks like.

The first step sets the baseline. The rest run continuously.

01 — Prompt research and baseline

Prompt research and baseline

We build the list of questions your buyers actually ask — vendor selection, category comparison, problem-first research — and run every one across the major assistants. We record whether you appear, what gets said about you, and who gets named instead.

02 — Make the site machine-readable

Make the site machine-readable

Schema markup, clean structure, and pages that state plainly what you offer. Assistants shouldn't have to infer what your company does from marketing language. Much of this overlaps with the technical work, which is why the two run together.

03 — Publish things worth citing

Publish things worth citing

Original data, direct answers to real questions, specific claims a model can attribute to you. Assistants cite sources that contribute something rather than sources that summarize what already exists.

04 — Build outside corroboration

Build outside corroboration

Media coverage, comparison lists, awards, and expert commentary. When several credible sources say the same thing about a company, assistants treat it as established. This is where AI visibility and media relations stop being separate programs.

05 — Re-run and track

Re-run and track

Monthly, on the same prompt set. Which answers changed, what you're now cited for, where competitors gained ground. Visibility moves, so the measurement has to be continuous rather than a one-time snapshot.

What you get

Deliverables, named.

Prompt set and baseline

The questions your buyers ask, with a recorded starting point for each across the major assistants.

Monthly visibility report

Where you're cited, where you aren't, and what changed since last month.

Competitor comparison

Who gets named in your category and what the assistants say about them.

Page and schema recommendations

Specific changes that make your content easier for models to parse and attribute.

Content targets

The topics and questions worth publishing on, chosen from gaps in the current answers.

Citation log

A running record of where you've been quoted or named, and what drove it.

SEO

Send us your domain.

We'll run your category's prompts before the call and show you exactly where you stand and who's being named instead.

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