Features of Contacts
This template enhances your data with standardized values and consolidates similar records into grouped entities.
About the Data Quality Services
The contacts template includes data quality services for these attributes:
The data quality process examines values for the template's attributes, and adds any resulting validated, standardized values to each record in new enrichment-specific attributes. These services also help identify additional communication channels, including which phone numbers can receive text messages. The original values mapped from your source datasets remain present and unchanged.
Note: By default, the validated and standardized business, or alternate, phone number data is used by the clustering model, but is not included in the final mastering flow output. You can modify the mastering flow to include additional fields. See Steps Completed by Contact Mastering.
See the topics linked above for processing details and added attributes.
About the Clustering Model
The contacts model groups contact records as follows:
First, by trusted_id. Records with the same trusted_id
are always clustered together. Records with different trusted_ids
are never clustered together.
Records with null/empty trusted_id
are clustered based on similarity, meaning that they may be clustered with records that have a trusted _id
.
Then, by similarity. Records with null or empty trusted_ids
are clustered based on similarities between values for these attributes:
- Name
- Street address
- Phone number
- User email
Note: Generic descriptions, rather than specific attribute names, are listed to represent both the standard schema and the attributes added by the enrichers and other data transformations.
Updated 12 months ago