Blueshift’s event processing easily ingests online and offline data from all data sources and internal systems, from across channels and devices. This is possible due to Blueshift’s schema-less architecture based on NoSQL technology that dynamically adapts to your data schemas, and takes care of the modeling so you always have a complete, up-to-date view of all your users. Our platform captures all data types, including behavioral, event, transactional, and user attributes.
As part of onboarding, you can set up a one-time import job to ingest your users' past historical transactional data (for example, purchases, subscriptions, and so on) so that you have a complete view of your users within Blueshift immediately. As such, with Blueshift, you have visibility of both the users' past and present behavior.
Blueshift helps you to better understand user interactions and affinities with your content. To achieve this, Blueshift provides the ability to easily import your content and product catalogs and measure/track user interactions with your content. Blueshift then uses this information to feed into our patented AI recommendation engine to personalize the most relevant content in future communications with your users.
Once the real-time data is ingested into Blueshift, this data is immediately available for use to drive downstream marketing processes, such as audience segmentation, 1:1 personalization, omnichannel campaign orchestration, sending data to paid media partners, or syncing data back to your internal systems to further influence and optimize your user experience.
Supported data formats
Due to Blueshift's unique and flexible architecture, we can accept data in any format (structured, semi-structured, or unstructured) and can properly index the metadata into the appropriate field for the appropriate user. No data modeling or data mapping is required. Blueshift can infer the incoming data, classify the data type (i.e., text, numeric, timestamp), and then automatically create data fields dynamically so that you always have a complete view of your users. You can also manually add, modify, and classify user data attributes directly within the Blueshift UI.
In the case of event data, you can easily add, modify, and classify any event activity for tracking user behavior across any channel in just a few clicks within the UI.
Supported data sources
Blueshift is data agnostic and can connect with any data source from across channels and devices. We have pre-built connectors with enterprise applications, such as a CRM, BI tools, data warehouses, helpdesk, ERPs, data lakes, and more to seamlessly ingest both real-time and batched data. Blueshift also has native integrations with leading ecommerce solutions, such as Magento and Shopify, to easily ingest customer, product catalog, and transactional data. The pre-built integrations streamline the implementation process and reduce the time to value to bring real-time event streaming data into Blueshift.
Blueshift supports both real-time data streaming and batch processing. Data can be ingested into Blueshift in a variety of ways:
- Using pre-built integrations with several tag management systems, such as Google Tag Manager, Tealium, and so on.
- Using pre-built integrations with customer data infrastructure systems, such as Segment, mParticle, and so on.
- For mobile behavioral user data, using the mobile SDK for integrating your Android and iOS mobile apps with Blueshift’s event processing platform.
- For data ingestion by integrating directly with your back-end systems, using the flexible and robust web services REST API to send user and behavioral data in real-time.
- From offline data sources, such as POS, in batched mode via flat file transfers (for example, Amazon S3, secure FTP, and so on) using one-time or recurring, automated import jobs.
For users' past historical transactional data, using a one-time import job.