Entity Optimization Playbook

Entity architecture fundamentals

AI systems identify and disambiguate entities to understand context. Your entity architecture determines how accurately AI systems can identify your brand, understand its attributes and evaluate its authority.

Step 1: Entity audit

Identify all entities associated with your brand: company, products, key people, locations, certifications and partnerships. Map how these entities currently appear across platforms.

Step 2: Entity definition

Define each entity with clear, consistent attributes. For your company: name, description, industry, founding date, headquarters, key offerings. Consistency across platforms is critical.

Step 3: Schema implementation

Implement JSON-LD structured data for each entity. Use Organization, Product, Person and LocalBusiness schemas. Ensure attributes match your defined entity data exactly.

Step 4: Knowledge graph mapping

Connect your entities to knowledge graphs — Wikidata, Google Knowledge Graph and industry databases. Cross-reference your entity definitions with existing knowledge graph entries.

Step 5: Relationship graph

Map relationships between your entities: company to products, company to key people, company to certifications, company to partners. These relationships help AI systems understand your organizational context.