engineer-user-data

Anonymous to identified user profile transitions in Braze require configuring external_id handling and alias support. This ensures proper profile lifecycle management and prevents data fragmentation when users authenticate across mobile and web platforms.

Choosing between custom events and attributes for Braze data collection involves applying a specific decision framework based on data type and query needs. Events track specific actions, while attributes capture persistent user profile states for segmentation.

Bulk user data imports to Braze via CSV, REST API (/users/track), or Cloud Data Ingestion require structured synchronization patterns. Configuring these workflows correctly ensures ongoing data accuracy and prevents duplication across server contexts.

Braze SDK data collection tiers for mobile and web are configured across minimum, default-on, and opt-in levels. Setting these tiers enforces data accuracy and compliance boundaries before any user attributes or events are captured.

Braze profile deduplication and merges require applying specific safety rules and best practices during data writing paths. Enforcing these rules prevents data corruption when consolidating multiple user identities or importing external data.

Braze Cloud Data Ingestion supports ongoing synchronization for server-side data across various contexts. It provides an alternative to direct REST API calls, automating continuous data import workflows without manual CSV uploads.