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Below is an overview of how to integrate with the Engage platform. It covers:
  • Available integration patterns
  • The authentication model
  • Key considerations for data synchronization and error handling
Use this section to consider the right integration approach before diving into the implementation details.

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Integration patterns

The Engage platform supports multiple integration patterns depending on use case, your data volume, and your latency requirements.
  • API: Synchronous, request-based access to platform data and operations. Suitable for real-time and transactional workflows where your system actively reads or writes data.
  • Webhooks: Event-driven notifications sent from Engage to your system. Used for reacting immediately to changes without the need for polling.
  • Technology partners: Using a pre-made integration with one of Engage’s many technology partners.
  • File-based imports: Scheduled or on-demand FTP batch imports using files.
  • File-based exports: Batch exports delivered as files via FTP, suitable for downstream systems that consume data from files.
  • Delta sharing: Incremental data access designed for analytics platforms and data lakes. Requires a dedicated setup and is updated once per day.
  • BI export: Curated analytical datasets, updated once per day. Used for datasets not yet available via delta sharing. Not intended for operational integrations.

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Authentication

Authentication in Engage works like this:
  • All integrations authenticate use API keys.
  • The API key is included in the request header for each API call.
  • Multiple keys can be created, but all keys currently have the same level of access.
  • Token-based authentication and scoped permissions are not supported.
  • Different integration patterns provide different guarantees concerning data freshness and consistency.
  • Engage does not support request-level idempotency. Duplicate prevention is handled through configurable duplicate control, where you define which customer attributes must be unique. Integrations should be designed with this in mind, particularly for retries or reprocessing data.

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Error handling

Error handling depends on the integration method used.
  • APIs require synchronous error handling per request.
  • Webhooks require validation and acknowledgement of incoming events.
  • Imports and file-based exports require monitoring of job execution and result files.
  • Delta sharing and BI export require validation of data completeness per refresh cycle.
More detailed guidance is provided in the respective sections.