With Blueshift's pre-built integrations, you can easily import data from multiple sources into Blueshift and export processed data to your connected systems and platforms. The data you send may include customer information, website or app events (such as user_identify, purchase, add_to_cart, etc.), and product details from your catalog. This unified data enables more relevant and consistent experiences across every customer interaction.
Blueshift’s pre-built integrations are easy to set up and require adding and validating the vendor’s authentication credentials in the integration settings within the Blueshift UI to enable these integrations.
Data integration capabilities
Blueshift provides comprehensive data integration across multiple data types. You can use the table below to explore import and export options for each data entity.
| Data type | Import | Export | Description |
|---|---|---|---|
| Customer data | ✓ Import | ✓ Export | User profiles, attributes, subscriber information, key historical conversion events, etc. |
| Events data | ✓ Import | ✓ Export | User interactions and behavioral data for analytics |
| Catalog data | ✓ Import | ✓ Export | Product or content catalog information |
| Campaign activity | — | ✓ Export | Campaign engagement metrics (sent, delivered, opened, clicked) |
| Recommendations | ✓ Import | — | Personalized content feeds |
| Segment members | — |
✓ Export
Via S3 or SFTP
|
List of users in segments for validation or integration |
| Predictive scores | — |
✓ Export
Via segments or syndications
|
AI-powered predictive scores for targeting and suppression |
| Syndications | — |
✓ Export
To paid media platforms
|
User data with attributes and insights to paid media partners |
| Reports & logs | — |
✓ Export
Via S3
|
Campaign reports, segment reports, and audit trail logs |
Data warehouse integrations
You can connect Blueshift with your enterprise data warehouse to import or export data as part of your data ecosystem. Supported warehouses include Amazon S3, Snowflake, Databricks, and Google BigQuery. For setup and configuration instructions, please refer to the data warehouses integration documentation.
Fair use and data retention
Blueshift’s fair use policy outlines how our systems should be used to ensure optimal performance and stability. Exceeding usage limits may result in additional costs. The data retention policy explains how event data is stored and indexed for segmentation. For more details, refer to the policy-related documentation.
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