Generate Organization Schema from B2B Company Data

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema

By dataclean.to team · 2026-02-05

B2B company databases contain business entity information including names, addresses, industry classifications, and corporate relationships. Organization schema provides structured representation of businesses, their hierarchies, and contact information. Proper organization markup improves knowledge panel display and business search visibility.

The Problem

Company databases store organizational hierarchies inconsistently and mix headquarters with branch locations. Legal entity names differ from trade names without clear distinction. Without Organization schema markup, search engines cannot display company knowledge graphs, understand parent-subsidiary relationships, or verify business legitimacy through structured identifiers like DUNS numbers or stock tickers. Schema.org Organization

How to Fix It

Extract Core Company Information

Parse legal name, trade names, and abbreviations. Extract founding date, tax identification numbers, and DUNS numbers. Identify company type (corporation, LLC, partnership) and jurisdiction.

Structure Contact and Location Data

Map headquarters address to location property with PostalAddress schema. Extract phone numbers, email addresses, and website URLs. Parse contact person information for key roles.

Parse Industry and Classification

Extract industry codes (NAICS, SIC) and business categories. Map to knowsAbout or industry properties. Include business descriptions and tag lines in description field.

Map Corporate Relationships

Identify parent companies, subsidiaries, and affiliated organizations. Use parentOrganization, subOrganization, and memberOf properties to represent corporate structure and partnerships.

Generate Organization Schema JSON-LD

Output Organization schema with required name field. Include legalName, address, telephone, url, foundingDate, and identifier properties with DUNS, stock ticker, or tax ID. Add logo and sameAs for social profiles.

Frequently Asked Questions

Should I use Organization or a more specific subtype like Corporation?

Use the most specific type available: Corporation for incorporated businesses, LocalBusiness for customer-facing locations, EducationalOrganization for schools, etc. The specific type enables richer search features tailored to that organization category.

How do I represent multi-location businesses in Organization schema?

Create a parent Organization for the brand with subOrganization properties linking to LocalBusiness schemas for each location. Alternatively, use location property with multiple Place objects if locations are not independently searchable.

What identifiers should be included in Organization schema?

Include official business identifiers using the identifier property with PropertyValue objects. Common identifiers: DUNS number, tax ID, stock ticker symbol for public companies, and LEI (Legal Entity Identifier) for regulated entities.

Example: Input → Output

name	address	city	phone	website
City Plumbing Co	789 Elm St	Denver CO	(720) 555-0200	cityplumbing.com
city plumbing co	789 elm st	denver	co	(720)555-0200	www.cityplumbing.com

Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.

{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "City Plumbing Co",
  "address": {"@type": "PostalAddress", "streetAddress": "789 Elm St", "addressLocality": "Denver", "addressRegion": "CO"},
  "telephone": "+17205550200",
  "url": "https://cityplumbing.com"
}

💡 How it works: LocalBusiness schema helps your listing appear in Google Maps and local search with structured contact info.

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