01 — Define

What do you want to be known for?

Map your expertise. Define your entities. Find the visibility opportunities worth going after.

→ Why starting with “what do I want to be known for?” changes everything
→ What a topic entity actually is — and how to identify yours
→ How to map expertise, audiences, and entity relationships
→ How to find the visibility gaps worth going after
→ How Define feeds the rest of the framework

Why this stage exists

This is the step most people skip — and it’s the most important one.

Most SEO programs start with keywords. You find what people are searching for, write content around it, optimize the page, and hope it ranks. That approach has worked for a long time.

But AI Search works differently. AI systems aren’t just matching search terms to pages — they’re building a picture of who is expert in what. They’re drawing on signals about entities, relationships, and associations to decide whose voice gets amplified in a response.

Which means the starting question is different. Not “what keywords should I target?” but what do I actually want AI to associate with my brand?

Define is the stage where you get specific. It’s the foundation everything else is built on.

The core concept

What is a topic entity?

An entity is any distinct, nameable thing — a person, brand, concept, location, product, or area of expertise — that AI systems can recognize and associate with other entities.

A topic entity is the specific subject area you want to own. Not a keyword. Not a category. A clearly defined concept that you want AI systems to reliably connect to your brand.

The difference between “SEO” (too broad), “AI Search Visibility” (a real topic entity), and “AI mention rate measurement” (a specific expertise area) is the level of specificity that makes visibility measurable and buildable.

Topic entities

The subjects you want to own

The specific concepts and subject areas that should reliably surface your brand in AI responses — named precisely, not broadly.

Expertise areas

What you actually know and how deep

The depth and context of your knowledge — what specifically you know, at what level, for what audiences.

Person & brand entities

Who is doing the work

The named people and organizations that should be associated with the topic entities — including you, your company, and key collaborators.

Audience entities

Who you serve and in what contexts

The specific audiences, use cases, and contexts where your expertise is most relevant — which shapes the queries you’ll measure against.

The questions to answer

Four questions that clarify everything else.

What do you want to be known for?

Not your tagline. Not your elevator pitch. The specific topics, expertise areas, and concepts that should reliably surface your brand in AI responses. The more specific your answer, the more useful it is as a foundation.

What expertise should be associated with your brand?

At what depth? In what contexts? For what audiences? An AI system that understands your brand should be able to describe what you know, not just who you are. What should that description include?

What topics deserve recognition?

Which subject areas do you have real, deep expertise in — the kind where you have original observations, documented experiments, and a track record? Those are the entities worth building visibility around.

Where are the visibility gaps?

What should AI systems be saying about you that they currently aren’t? Where does your expertise go unrecognized? What associations are missing, wrong, or muddier than they should be? That gap is where the opportunity is.

How to do it

From fuzzy to specific — the Define process.

01

Start with what you want to own, not what you already rank for

Keyword rankings are a starting point, not a destination. List the topic areas where you have genuine, deep expertise — the ones you’d be confident talking about for an hour without notes. Those are your candidate topic entities.

02

Get specific — then get more specific

“SEO” is not a topic entity. “AI Search visibility” is better. “AI mention rate measurement” is specific enough to be useful. Push each candidate topic through rounds of specificity until you land on something that’s clearly bounded and distinctly yours.

03

Map the relationships between entities

Your topic entities don’t exist in isolation. They connect to each other, to your brand, to your audience entities, and to the broader knowledge graph. Sketch those connections — they become the architecture for the Structure stage.

04

Identify the gaps — where you should be recognized but aren’t

Run a baseline mention rate check for your top topic entities. Where does AI currently associate you with these topics? Where is the recognition weaker or missing entirely? Those gaps become your visibility priorities for everything that follows.

What comes next

Define feeds everything else.

The output of Define isn’t a document. It’s a set of clearly defined entities — topic areas, expertise associations, and entity relationships — that become the foundation for every decision in the next three stages.

Structure takes those entities and gives them homes on your site. Reinforce takes them and builds the external signals that validate them. Measure takes them and tests whether AI systems are actually recognizing them.

Without a clear Define output, the other three stages are building on a fuzzy foundation. That’s why this stage comes first — and why getting the specificity right here is worth more time than most people give it.