May Update

Marketers often struggle to act on complex, behavior-based insights— such as  combining purchase data across categories, channels, and timeframes, without relying on data teams.

To solve this, Blueshift is introducing Computed Attributes: dynamic, self-serve fields that marketers can create using flexible, no-code configurations. These attributes automatically update based on real-time event data and can be used across segmentation, personalization, journey triggers, and reporting—enabling smarter, faster marketing without the wait.

You can now define and create custom profile attributes in the Data Studio using event and catalog data, functions, and filters within a set timeframe. With computed attributes, you can:

• Calculate new customer attributes based on event and product attributes data.
• Segment users, build journeys, and analyze customer profiles using custom attributes computed daily.
• Increase precision in targeting and launch more relevant, high-impact campaigns.
• This enhancement offers greater flexibility and control over customer data, empowering you to deliver smarter segmentation and more personalized experiences.

Note: This feature is currently available only in the US region.

RFM is a proven marketing framework that is based on the recency, frequency, and monetary value of each customer’s behavior. It is used across retail, e-commerce, travel, and financial services to prioritize and personalize engagement. Blueshift now offers built-in RFM scoring using the data already flowing through the platform.

You can now view and utilize RFM scores and segmentation to better understand and target your customers. RFM (Recency, Frequency, Monetary) scores help you:

• Identify high-value customers based on purchasing behavior.
• Optimize targeting for promotions and engagement campaigns.
• Increase ROI by focusing on active customers and retargeting disengaged ones.

Each RFM score combines three components, rated from 1 to 5:

• Recency – How recently a customer made a purchase
• Frequency – How often a customer makes a purchase
• Monetary – How much a customer spends

Customers are assigned a combined RFM score and categorized into segments based on engagement and value. This analysis enables intelligent, precise segmentation and more effective marketing strategies.

Note: RFM scores are available for e-commerce and retail customers who have ‘purchase’ events in the past year. Other customers can contact their CSMs to enable this feature on their accounts.

Customer attributes are now grouped into standardized categories—standard, derived, predictive, custom, and computed. These changes are reflected in attribute selection dropdowns for building segments, journeys, reports, and other workflows. This update makes it easier to browse and select the appropriate attributes.

Segmentation in the platform just got easier and faster! You can now build segments by selecting actions on templates and links, without manually specifying campaigns or triggers. With this update, you can:

• Choose to segment by template or link interaction.
• Filter users who interacted with specific templates or links without needing to select campaigns.
• Create segments based on link behavior and filter users using either indexed links or conditional link matching criteria.

This enhancement simplifies segmentation workflows and gives you greater flexibility to create precise, targeted audiences based on user interactions.

To improve email tracking and management, we are introducing a new core metric – Native BCC sends. It is now available to help you track emails sent using the native BCC method. This metric appears in:

• Insight and Campaign reports
• Campaign and template index pages
• The Plan & Usage screen (displays Native BCC sends separately)

The existing BCC sends metric remains unchanged. The new Native BCC sends metric is available only if the Native BCC feature is enabled for your account. For more information, please refer to the Send copies of email article.

You can now generate self-serve reports from the Data Studio to view where customer attributes are used across Blueshift entities such as campaigns, segments, and templates. This enhancement makes it convenient to analyze attribute usage and manage your customer data more effectively.

We are introducing a new update to ensure responsible data sharing without compromising performance. When syndicating data to paid media destinations, you can now exclude specific personally identifiable information (PII) attributes. A new ‘Exclude PII Data’ section in the adapter setup allows marketers to select attributes they want to exclude. The list of available attributes is destination-specific, and any attributes excluded will not be included in the syndicated data. This update enhances data privacy and provides greater control over the information shared with external platforms.

When uploading a CSV file for a promotion, you can now preview the first 10 rows from the uploaded file before submitting. Before finalizing the upload, this preview helps you quickly validate the uploaded data.

We have updated the Blueshift color palette for a refreshed and consistent visual experience.

Journey builder trigger filters now support nested attribute filtering in the same way as segmentation filters. This ensures that conditions on nested objects, such as devices or preferences, are evaluated correctly, improving the accuracy of audience targeting.

You can now select the date-time format and time zone when configuring file imports across Blueshift. This update supports multiple date formats and time zones. It is available for customer, event, and recommendation feed imports. When setting up or editing imports, you can choose the preferred format and time zone for imported timestamps, reducing the need for manual data conversions.