Segments in Salesforce Data Cloud
In this blog, we will take a closer look at Segments in Data Cloud. It is one of those features that many people hear about but often overlook until targeting, analysis, or activation starts becoming difficult. Segments in Data Cloud help you organize customer data into meaningful groups and use those groups across different platforms when needed.
Just like you would not run a campaign without clearly knowing your audience, businesses cannot rely on raw data without structuring it properly. Segments make this possible by turning scattered data into clear and actionable groups.
What Are Segments in Data Cloud?
Segments in Data Cloud are dynamic customer groups built directly from your unified data model. They allow you to understand different types of customers, analyse their behaviour, and publish those audiences to activation targets such as marketing platforms, analytics tools, or operational systems.
Segments also give you powerful flexibility. You can build them using the attribute library, enhance them with calculated insights, and refine them with filter criteria. Whether the segment is simple or complex, the process supports all downstream use cases — from campaigns and personalization to reporting and automation.
Note: Salesforce Data Cloud is now referred to as Data 360 as part of the broader Agentforce 360 initiative.
Types of Segments in Data Cloud
There isn’t just one way to build a segment. You can choose different types depending on how fast you need results, how you plan to use the data, and whether the segment will stay static or change dynamically.
Standard Segment in Data Cloud
A standard segment starts with choosing a data model object. You give it a name, select a “Segment On” object, and define the lookback period. The system defaults to 90 days, but it can go up to two years depending on your organization’s configuration.
Keep one thing in mind with lookback. If the segment-level lookback is set to 90 days but a filter container uses 60 days, the container rule wins.
You can then choose whether to publish using Standard Publish or Rapid Publish and set how often it runs. You can preview your audience before saving, which helps ensure accuracy before activation. Salesforce allows up to 9,950 segments maximum.
Real-Time Segment in Data Cloud
Real-time segments in Data Cloud are complete on demand and in milliseconds. To make these segments part of your real-time data graph, add the Segment ID and Timestamp fields from the segment membership object. Real-time segments come with some limitations: no exclusion criteria, no nested batch segments, and no segment counts or manual publishing. They’re designed to return results instantly, not for advanced logic.
Waterfall Segment in Data Cloud
A waterfall segment is used when you want to process existing segments in priority order. This ensures that someone who qualifies for multiple segments lands only in the highest priority one. It creates mutually exclusive audiences, which is useful when you want each customer to receive just one relevant message or offer.
Waterfall segments allow up to 20 segments. They can include only active segments based on the selected object, and they can’t be nested or used in multiple waterfalls. Rapid publish is not available for waterfall segments.
Dynamic Segment in Data Cloud
Dynamic Segments in Data Cloud let you run segmentation queries without storing membership data. You set up filters with placeholders, and the actual values arrive at runtime. These segments aren’t published or scheduled in the interface. They’re triggered through an API call using broadcast flow and still support lookback logic similar to standard segments.
Segment from a Data Kit
Instead of building from scratch, you can choose a predefined segment from a data kit. This gives you a starting point that you can edit and fine-tune. You choose the segment, check for dependencies like child segments or insights, define details, and schedule publishing.
How Segmentation Publishing works in Data Cloud?
Once a segment is defined, you can publish it manually or based on a schedule you set. Standard publishing typically runs every 12 or 24 hours. When too many segments publish at the same time, Data Cloud queues and defers others until capacity frees up. That means a segment might not always publish at its exact scheduled moment if the system is at concurrency limits.
Increasing Segment Refresh
Rapid Publish updates segments more frequently, every one to four hours, but only looks at the last seven days of engagement data. Rapid segments take priority over standard ones, cannot be converted from an existing standard schedule, and are limited to 20 per org. These segments can be activated to Marketing Cloud Engagement and file storage targets.
Rapid refresh also supports incremental mode, indexing based on profile ID.
Understanding Segment Types, Statuses and Schedules
You can build segments through the UI or the API, and they appear as either UI or DBT segments. Segment Status shows whether a segment is active, processing, recounting its audience, in error, or inactive. Publish Status indicates whether the publish succeeded, failed, was skipped, is still in progress, or was deferred.
Publish schedules include options such as hourly (for rapid), every 12 or 24 hours, or no refresh at all. Manual publishing takes priority over scheduled runs.
Segment Membership Data Model Objects
Each publish creates or updates membership objects that store the audience list. There are two types:
- Latest — current audience after publish
- History — previous audience within the last 30 days
When someone no longer meets the criteria, they’re removed during the next publish. You can view membership data in Data Explorer, download it into Tableau, or query it with SOQL or APIs.
The Segment Canvas: Where You Build the Logic
The Segment Canvas in Data Cloud helps you build your audience by adding attributes, either direct or related. Direct attributes are single data points, like a first name or birthday, while related attributes include multiple data points, such as orders or interactions.
Object relationships determine what appears in the library. Some relationships are created automatically based on match and reconciliation rules. Linking is case-sensitive, and exact matching matters when joining paths.
Segment counts show how many entities meet your criteria. For dynamic segments with parameter values, this may not apply. Primary and foreign keys don’t display in the canvas, but you can create custom attributes if needed.
Filters sit inside containers and use operators that match the attribute type. Approximate population helps estimate quickly and adjust rules before saving.
You can filter by business unit, view multiple rulesets for identity resolution, enable value suggestions for up to 500 attributes, and honour publish time zones.
Einstein Segments in Data Cloud
Einstein Segments in Data Cloud let you describe the type of audience you want and get a suggested segment with relevant attributes. It uses sample data to ground suggestions without exposing PII.
The system blocks biased or unethical descriptions and automatically deselects demographic attributes that could introduce bias. You enable Einstein segments first, then describe the audience and adjust results, especially when results appear unclear.
Troubleshooting Segments in Data Cloud
Common issues include segments referencing too many data objects, being too complex, returning skewed data, or being inactive. Solutions include simplifying rules, using calculated insights, merging containers, or waiting for processes to finish. Date filters, time zones, and identity resolution changes can impact population counts.
Billing Considerations
Segmentation consumes credits based on the amount of processing and how frequently segments refresh. Storage tracks and retains the output from each run. Using preview, reducing schedule frequency, refining lookback windows, or limiting end dates can help reduce consumption.
Salesforce continues to introduce new ways to enhance automation and intelligence across the platform. If you’re curious about how Salesforce is extending these capabilities beyond segmentation, learn more about the Agentforce 360 here
FAQs
1. What is a segment in Salesforce Data Cloud?
Segments in Data Cloud are dynamic groups of customers created from your unified data. They help you understand customer behaviour and make it easy to activate those audiences across marketing, analytics, and operational platforms.
2. How to create a standard segment in Salesforce?
In Data Cloud, go to Segments and click New. Choose Use a Visual Builder, select Standard Segment, and then click Next to enter the required details.
Also Read – Top Flow Features in Salesforce Spring ’26 Release
Conclusion
Segments in Data Cloud give you control, flexibility, and insight directly from your data model. Whether you’re building real-time logic, mutually exclusive audiences, dynamic API-based queries, or scheduled refreshes, segmentation shapes how you understand and activate your customer data — in a way that fits the scale and speed your business needs.
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