Entity-Based Keyword Research: How to Map Topics for LLM Visibility

Traditional keyword research focuses on search terms. Entity-based keyword research focuses on concepts, relationships, and the way AI search engines understand topics. It's the foundation of LLMO and a critical skill for anyone optimizing for AI visibility.

This guide teaches you how to identify entities, map their relationships, and structure keyword research around entity networks that AI engines recognize and reward.

What Are Entities in AI Search?

An entity is a distinct, well-defined concept that AI engines recognize and categorize. Unlike keywords (which are text strings), entities represent real-world things.

Examples of entities:

• Products: iPhone, Slack, Google Analytics
• People: Elon Musk, Neil Patel, Tim Ferriss
• Concepts: SEO, conversion rate optimization, content marketing
• Places: San Francisco, Silicon Valley, New York
• Organizations: Google, OpenAI, Shopify

Each entity has attributes (properties) and relationships to other entities. For example, the entity "Shopify" has attributes like "e-commerce platform," "monthly pricing," and relationships like "alternative to WooCommerce" or "integrates with Stripe."

Why Entities Matter for AI Visibility

AI engines don't see your content as a collection of keywords. They parse it as a network of entities and relationships. When you optimize for entities, you:

1. Help AI Understand Context

If you mention "Apple," does it mean the fruit or the company? Entity-based optimization clarifies context through related entities (iPhone, MacBook) and attributes (tech company, founded 1976).

2. Trigger Semantic Connections

AI engines connect your content to related topics. If you write about "email marketing," AI links your content to entities like "Mailchimp," "conversion rates," "A/B testing," and "newsletters."

3. Improve Citation Likelihood

AI engines prefer content that comprehensively covers entity attributes and relationships. A page about "Shopify" that covers pricing, features, alternatives, and integrations is more citation-worthy than one that only lists features.

4. Rank for Variations Automatically

When you optimize for the entity "content marketing," you naturally rank for related queries like "what is content marketing," "content marketing strategies," and "content marketing vs advertising."

How to Identify Entities in Your Niche

Start by listing the core entities in your topic area. Use these categories:

Mapping Entity Relationships

Once you've identified entities, map how they relate to each other. Common relationship types:

Hierarchical Relationships

"Email marketing" is part of "digital marketing." "Mailchimp" is a type of "email marketing software."

Comparison Relationships

"Mailchimp" vs "ConvertKit." "Email marketing" vs "social media marketing."

Attribute Relationships

"Mailchimp" has attributes: pricing, features, integrations, ease of use, customer support.

Use Case Relationships

"Email marketing" is used for lead nurturing, product launches, customer retention, re-engagement campaigns.

Alternative Relationships

"ConvertKit" is an alternative to "Mailchimp." "SMS marketing" is an alternative to "email marketing."

AI engines use these relationships to understand context and connect your content to relevant queries. When you explicitly cover these relationships, you increase visibility.

Building Content Around Entity Clusters

Entity-based keyword research naturally leads to topic clusters. Here's how to build content around entity maps:

Create a Pillar Page for Each Core Entity

Your pillar page should comprehensively cover the entity, its attributes, and its primary relationships. For "email marketing," this means defining it, explaining its benefits, comparing it to alternatives, and listing tools.

Build Supporting Pages for Attributes

Each significant attribute becomes a supporting page. For "email marketing," you might create pages on "email open rates," "email segmentation," "email automation," and "email copywriting."

Cover Comparison Queries

Create dedicated comparison pages for high-value entity pairs: "Mailchimp vs ConvertKit," "email marketing vs social media marketing."

Link Entities Contextually

When you mention an entity in your content, link to the page that covers it comprehensively. This helps AI engines understand entity relationships and navigate your content network.

For more on this, see our guide on building question clusters and structuring content for AI search.

Frequently Asked Questions