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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 data generates Schema.org Organization markup for business entities. Automated schema generation processes company names, addresses, contacts, and identifiers. This tool converts spreadsheet data into structured JSON-LD that follows schema requirements for business visibility.

The Problem

B2B companies maintain organization data across CRM systems, vendor databases, and partner portals with inconsistent formatting. Company names, legal entities, addresses, and contact details vary in structure. Manual schema creation for hundreds of organizations takes excessive time. Automated generation ensures consistent structured data while maintaining relationships to parent companies, subsidiaries, and business identifiers that follow schema specifications. Schema.org Organization Specification

How to Fix It

1
Upload Company Data
Import CSV or Excel files containing organization information including name, legal name, address, contact details, and identifiers. System identifies organization-specific fields.
2
Configure Organization Mappings
Map columns to Organization properties like name, legalName, address, contactPoint, url, logo, identifier, and parentOrganization relationships.
3
Validate Company Data
System checks address formats, validates URLs and email addresses, ensures phone number formatting, and verifies business identifier structures like DUNS.
4
Generate Organization Schemas
Tool creates JSON-LD for each company with proper nesting of address, contact points, organizational hierarchy, and social media profiles.
5
Export and Implement
Download individual organization schemas or bulk export all generated JSON-LD files ready for website implementation.

Frequently Asked Questions

What organization properties are required?
Only name is required. Recommended additions are address, telephone, url, logo, contactPoint, sameAs for social profiles, and identifier for business IDs.
How do I represent corporate hierarchies?
Use parentOrganization and subOrganization properties to link entities. Each organization should have unique identifier and its own schema markup.
Can I include multiple contact points?
Yes, contactPoint accepts array of ContactPoint entities with different contactType values like "customer service", "sales", "technical support" each with telephone and email.

Example: Input → Output

nameaddresscityphonewebsite
City Plumbing Co789 Elm StDenver CO(720) 555-0200cityplumbing.com
city plumbing co789 elm stdenverco(720)555-0200www.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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