Enrich entity identifiers (emails, phones, addresses) with demographic, behavioral, and interest data.

Step 1: Resolve Identifiers

Convert identifiers to entity IDs. See entity_resolve for full parameter details.

{
  "entity_type": "person",
  "identifiers": [
    { "id_type": "email", "hash_type": "plaintext", "values": ["customer1@example.com"] },
    { "id_type": "phone", "hash_type": "plaintext", "values": ["5551234567"] }
  ]
}

Multiple identifier types improve match rates. Check stats.rate in the response; filter resolved entities by overall_quality_score >= 0.5. For large lists, use csv_resource_uri instead of inline values.

Step 2: Enrich Entity Profiles

Retrieve profile data for resolved entity IDs. See entity_enrich for available domains and full parameter details.

{
  "entity_type": "person",
  "entity_ids": ["12345", "12346"],
  "domains": ["demographic", "interest", "affinity", "lifestyle", "household", "financial"],
  "workflow_id": "550e8400-e29b-41d4-a716-446655440000"
}

Request only the domains you need. entity_enrich accepts up to 1,000 entity IDs per request — batch larger lists.

Alternative: Bulk Row-Level Enrichment

For CSV-based workflows that need 1:1 row correspondence, use resolve_and_enrich_rows to combine resolution and enrichment in a single operation.

{
  "entity_type": "person",
  "csv_resource_uri": "workflow://550e8400.../uploads/customers.csv",
  "email_columns": ["email"],
  "phone_columns": ["phone"],
  "domains": ["demographic", "interest", "affinity"],
  "workflow_id": "550e8400-e29b-41d4-a716-446655440000"
}

Related guides:

• ICP Analysis
• Criteria-Based Audiences