Field Mapping

Map your columns to schema properties for JSON-LD generation.

How Mapping Works#

After selecting a schema template, you'll map each relevant column in your data to a Schema.org property. We automatically suggest mappings based on column names.

Your Columns

Schema Properties

JSON-LD Output

Required vs Optional Fields#

Each schema type has required and optional fields. Google uses required fields to determine if your markup is valid for rich results.

LocalBusiness Example

Schema FieldRequiredYour Column
nameRequiredbusiness_name
addressRequiredstreet, city, state
telephoneOptionalphone
openingHoursOptionalhours

Nested Objects#

Some properties require nested objects (like address). We automatically structure these from your flat column data.

Your Columns
Input
street: "123 Main St"
city: "Austin"
state: "TX"
zip: "78701"
Generated JSON-LD
Output
"address": {
  "@type": "PostalAddress",
  "streetAddress": "123 Main St",
  "addressLocality": "Austin",
  "addressRegion": "TX",
  "postalCode": "78701"
}

Validation#

We validate your mappings against Schema.org specifications and warn about missing required fields before export.

Valid: All required fields mapped

Your schema is complete and ready for export

Warning: Optional field missing

Adding "telephone" could improve rich result eligibility

Error: Required field missing

Map "name" to a column to enable export

Note
Auto-mapping matches column names like "business_name" to schema properties like "name". You can always override or adjust these mappings.
Schema TemplatesAPI Authentication