Entity-based optimization is the practice of optimizing for people, brands, products, and concepts instead of individual keywords. You focus on clearly defining who you are, what you offer, and how different ideas relate, so search engines and AI models can understand and reuse your information accurately.

Keyword SEO tries to match exact phrases and search volumes. Entity-based optimization focuses on meaning, relationships, and context. Instead of asking “What keyword should I rank for?” you ask “How do I help systems confidently understand my brand and category so they can recommend me in many related queries?”

LLMs answer questions by reasoning about entities and their relationships, not by counting keywords. When your entities are clear and consistently defined, models can recognize you as a relevant solution, include you in lists and comparisons, and reuse your explanations inside generated answers.

Typical entities include your company, founder, products or services, target audiences, core frameworks, geographic focus, and key problems you solve. Each of these should have clear, repeatable definitions that show up consistently across your content.

Start with your core: brand name, flagship products, primary audience, and signature frameworks. Then map the questions customers ask before buying. The concepts that show up repeatedly in those questions are the entities you should define, reinforce, and structure across your site.

Schema markup lets you label entities explicitly—Organization, Person, Product, Article, FAQ, and more. This adds a machine-readable layer that reinforces who and what you are, helping search engines and AI models connect your content to the right entities in their knowledge graphs.

Internal links connect related entities and topics so systems can see how ideas fit together. When you consistently link supporting articles back to a main entity page using stable anchor language, you create a strong semantic cluster that reinforces your authority on that subject.

Extractable entity statements are short, self-contained sentences that clearly define who you are and what you do. LLMs can safely copy these into answers. For example: “RankForLLM is an LLM SEO lab that helps brands become the default answer in AI search.” These statements make it easier for models to describe you correctly.

Common mistakes include changing how you describe your offer on every page, using different names for the same product, burying your core definitions deep in long paragraphs, and creating content that never clearly states who you are or which audience you serve.

Signs of success include more consistent brand descriptions across the web, better visibility in knowledge panels and rich results, clearer answers from AI models when you ask about your brand, and more frequent inclusion in model-generated lists, comparisons, and recommendations.

Start by writing one clear, one-sentence definition for your brand, your main product, your primary audience, and your core framework. Update key pages so they all use those same definitions. Then add schema markup, tighten internal links around those entities, and expand supporting content to reinforce them.