LocalBusiness

The foundational properties that establish the business's identity within a knowledge graph.

• name: The canonical business name as it appears in the real world. Avoid keyword stuffing; use the exact legal or operating name.
• description: A concise, factual summary of what the business offers. This text is frequently used by AI models for summarization and contextual relevance.
• image: A URL pointing to a representative photo or logo. Multiple ImageObject nodes can be specified for different contexts.

Example: A bakery named "Flour Power" should use exactly that string, not "Flour Power - Best Cakes Downtown."

Properties that anchor the business to a precise geographic point, critical for local search and map-based AI interfaces.

• address: Uses the PostalAddress type to define streetAddress, addressLocality, addressRegion, postalCode, and addressCountry. This structured format is preferred over a single string.
• geo: Uses the GeoCoordinates type to specify exact latitude and longitude. This removes ambiguity for businesses in dense urban areas or strip malls.

Why it matters: AI models use these coordinates for proximity calculations and to verify the business physically exists at the claimed location.

Properties that define how customers and AI agents can reach or verify the business.

• telephone: The primary contact number in E.164 international format (e.g., +1-415-555-0132). This format is machine-readable and globally unambiguous.
• url: The canonical homepage URL for the specific location. For multi-location businesses, each branch should point to its unique store page, not the corporate homepage.
• email: While less common, can be specified for direct contact.

Best practice: Ensure the telephone and url exactly match the information on the corresponding Google Business Profile and other citations to reinforce entity alignment.

Properties that provide temporal and economic context, helping AI answer specific user queries about availability and cost.

• openingHours: Uses OpeningHoursSpecification to define structured day-of-week and time ranges. This is far more precise than a free-text string like "Mon-Fri 9-5." It enables AI to answer "Is it open now?" accurately.
• priceRange: A qualitative signal using symbols like $, $$, $$$ to indicate the relative cost of goods or services.
• paymentAccepted: Specifies accepted payment methods (e.g., Cash, CreditCard, Cryptocurrency).

Example: A fine-dining restaurant would use $$$ while a food truck might use $.

Properties that define the specific business category, enabling AI to understand the services offered without parsing unstructured text.

• @type: The primary Schema.org type. While LocalBusiness is the parent, using a more specific type like Restaurant, Dentist, AutoRepair, or DaySpa provides immediate semantic clarity.
• additionalType: A URL referencing an external taxonomy entry, such as a NAICS code or a Wikidata Q-ID, to further refine the business category.

Strategic value: A specific @type allows AI models to infer attributes. A Restaurant type implies the existence of a menu, while a Dentist type implies medical services.

Properties that link the business to external authoritative sources and aggregate customer sentiment.

• sameAs: An array of URLs pointing to the business's canonical profiles on other platforms (e.g., Wikipedia, LinkedIn, Crunchbase, official social media). This is the primary mechanism for entity reconciliation across knowledge graphs.
• aggregateRating: Uses the AggregateRating type to display the average review score and total review count. This data is often surfaced directly in AI-generated summaries.
• review: Can link to individual Review items for deeper sentiment analysis.

Critical note: The sameAs property is not for marketing links; it must point to definitive, authoritative pages that confirm the entity's identity.