Organization schema markup tells search engines exactly what your company is, what it does, and how it connects to the broader web. When implemented correctly, this structured data helps Google's Knowledge Graph recognize your business as a verified entity—increasing chances for Knowledge Panel visibility and AI search citations.
This guide provides step-by-step instructions for implementing Organization schema that supports Knowledge Graph inclusion.
Google's Knowledge Graph relies on verified, structured data to understand entities. Organization schema provides that structure in a format search engines process directly.
According to ALMCORP's schema markup guide, schema markup makes the content ready to feed into Google's Knowledge Graph and other AI systems. The more accurate and structured your data, the more confidently algorithms can surface your brand in Knowledge Panels, AI Overviews, and LLM outputs.
Organization schema benefits:
Not all Organization schema properties carry equal weight. Focus on required properties first, then add recommended properties for comprehensive coverage.
| Property | Purpose | Example |
|---|---|---|
| @type | Entity type classification | Organization, Corporation, LocalBusiness |
| name | Official organization name | "Acme Corporation" |
| url | Official website URL | "https://www.acme.com" |
| Property | Purpose | Knowledge Graph Impact |
|---|---|---|
| logo | Organization logo image | Displays in Knowledge Panel |
| sameAs | Links to authoritative profiles | Validates entity across sources |
| description | Organization description | Populates Knowledge Panel text |
| foundingDate | When organization was founded | Adds entity context |
| founder | Who founded the organization | Creates entity relationships |
| Property | Purpose |
|---|---|
| address | Physical location |
| contactPoint | Customer service, support contacts |
| numberOfEmployees | Company size indicator |
| areaServed | Geographic service area |
| parentOrganization | Corporate structure relationships |
JSON-LD is the recommended format for Organization schema. It separates structured data from HTML content and is easier to maintain.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Company Name",
"url": "https://www.yourcompany.com",
"logo": "https://www.yourcompany.com/images/logo.png",
"description": "Brief description of what your organization does.",
"foundingDate": "2015",
"sameAs": [
"https://www.linkedin.com/company/yourcompany",
"https://twitter.com/yourcompany",
"https://www.facebook.com/yourcompany"
]
}
For maximum Knowledge Graph impact, include all relevant properties:
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Company Name",
"alternateName": "YCN",
"url": "https://www.yourcompany.com",
"logo": {
"@type": "ImageObject",
"url": "https://www.yourcompany.com/images/logo.png",
"width": 600,
"height": 60
},
"description": "Your Company Name is a leading provider of...",
"foundingDate": "2015-03-15",
"founder": {
"@type": "Person",
"name": "Jane Smith"
},
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Business Street",
"addressLocality": "San Francisco",
"addressRegion": "CA",
"postalCode": "94102",
"addressCountry": "US"
},
"contactPoint": {
"@type": "ContactPoint",
"telephone": "+1-555-123-4567",
"contactType": "customer service",
"availableLanguage": "English"
},
"sameAs": [
"https://en.wikipedia.org/wiki/Your_Company",
"https://www.wikidata.org/wiki/Q12345678",
"https://www.linkedin.com/company/yourcompany",
"https://twitter.com/yourcompany",
"https://www.crunchbase.com/organization/yourcompany"
]
}
The sameAs property connects your organization to authoritative external sources—a key signal for Knowledge Graph inclusion.
According to Search Engine Land's entity markup guide, entity-based structured data markup, particularly the sameAs property, helps fix AI hallucinations by clearly defining your entity's authoritative sources.
Tier 1 (Highest Impact):
Tier 2 (Strong Impact):
Tier 3 (Supporting):
Before writing markup:
Use the templates above as starting points. Customize with your organization's specific data.
Place JSON-LD in a script tag in your page's <head> section:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Organization",
...
}
</script>
Placement options:
According to Backlinko's schema guide, always validate your JSON-LD using Google's Rich Results Test before deployment.
Validation tools:
After implementation:
| Error | Solution |
|---|---|
| Invalid JSON syntax | Use JSON validator before deployment |
| Missing @context | Always include "https://schema.org" |
| Wrong @type | Use most specific applicable type |
| Broken sameAs URLs | Audit and remove dead links |
Organization schema markup is foundational for Knowledge Graph optimization:
Start with required properties - name, url, and @type form the minimum viable markup
Prioritize sameAs links - Connections to Wikipedia, Wikidata, and verified profiles strengthen entity validation
Use JSON-LD format - Recommended by Google, easier to maintain, separates data from HTML
Validate before deploying - Test markup with Google's tools to catch errors before they affect indexing
Maintain accuracy - Schema must match reality across all linked sources—inconsistencies weaken signals
According to Addlly.ai's schema research, well-optimized schema markup improves search engine understanding, helping your content get picked up by AI search results and increasing visibility in Knowledge Panels.
Implement Organization schema correctly, and you create a machine-readable foundation for Knowledge Graph recognition—essential for both traditional search visibility and emerging AI search platforms.
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