You can create custom text fields that store external IDs or other unique, record-specific values. 

You can use these external IDs when data comes into Slate—through an import or a form submission—to match the incoming record to an existing one in your database. These fields play a critical role in integrations, like when you import data from external systems with unique system IDs into Slate.

The Unique for Merging setting

When you create a new field, you’ll find a setting in the Details tab called Unique for Merging.

For text fields, the default value for this setting is Do not use value for merging.

When you change this value to Value contains a unique ID which identifies a single record for merging, Slate uses the incoming field’s value to match against existing records in its scope.

Example unique for merging fields

Say you have a nine-character text field called Unique ID.

If a record has a value of 123456789 in this field, and its unique for merging setting was set to Value contains a unique ID which identifies a single record for merging, no other record in that dataset could have that same value.

If another record entered the Dataset that had this field set to a value of 123456789, Slate would merge that record with the existing record with that value.

Unique for merging and Consolidate Records

The Consolidate Records tool uses unique for merging fields to find potential matching records.

Configure a custom, unique for merging field only if each record is guaranteed to have a unique value for the field.

Examples of unique custom fields include:

• SIS ID 

• Banner ID 

• EmplID 

• ColleagueID

• CommonApp ID 

• Questbridge ID

📖 Further reading: Consolidate Records

Mapping data imports to multiple unique for merging fields

Exercise caution when you map data imports to multiple unique for merging fields. The import may use any of the unique for merging fields to match a candidate application or person.

Similarly, collecting values publicly (that is, through a public-facing form) to unique for merging fields can result in record collisions if transcription errors occur.

Slate has a clearly-defined hierarchy of criteria by which it matches records. Knowing how this works will help avoid unexpected behavior on record imports.

📖 Further reading: matching criteria

Learn more about matching criteria as they relate to different kinds of objects in these articles:

• Matching Criteria for Application Records

• Matching Criteria for Person Records

• Matching Criteria for System Objects