Data Activations and Utilization20% of the exam
Segmentation concepts: attributes, containers and population
What segmentation is for and how the segment canvas thinks: Segment On, the attribute library, direct versus related attributes, containers and filter logic, population counts and preview, and building segments from natural language with Einstein segments or the Data 360 Marketing Agent.
Define basic concepts of segmentation and use cases.
~8 min read · 10 practice questions ·
What the exam expects
- Recognize what segmentation is for (targeted audiences, mutually exclusive offers) and which tasks belong to identity resolution or data modeling instead.
- Explain why an object can or can't be chosen for Segment On, and why a mapped field can be missing from the attribute library.
- Classify an attribute as direct or related and predict what one container versus separate containers returns.
- Explain when the population count updates, who can preview a segment, and how filter values treat case.
- Recommend Einstein segments or the Data 360 Marketing Agent when a marketer wants to describe an audience in plain language.
Key terms:
- Segment On: the target object whose distinct records form the audience.
- Attribute library: the attributes mapped in the data model and marked for use in segmentation.
- Direct attribute: one data point per segmented record, such as postal code.
- Related attribute: many data points per record, such as purchases or email opens.
- Container: a group of related-attribute conditions evaluated against the same related records.
Key facts
Segment On eligibility
- Detail
- Objects marked Profile or Engagement type during ingestion
Lookback Window
- Detail
- Default 90 days; up to 2 years (360 in Days); container window wins
Attribute library
- Detail
- Depends on the Segment On object
Attribute eligibility
- Detail
- Mapped in the data model and marked for use in segmentation
Keys on the canvas
- Detail
- Primary and foreign keys don't appear
Filter values
- Detail
- Not case sensitive
Container path joins
- Detail
- Case sensitive, not configurable
Sum, Average, Max, Min
- Detail
- Numeric data only; Count works on any type
Population refresh
- Detail
- After publishing or an on-demand count
New filter or container count
- Detail
- Shows Calculate population until refreshed
Preview access
- Detail
- Segment view or edit rules permissions plus Data Explorer access
Einstein segments filtering
- Detail
- Bias-prone demographics deselected; attributes under 10 results removed
Sources for this section (6)
- Create a Standard Segmenthelp.salesforce.com (opens in a new tab)
- Segment Onhelp.salesforce.com (opens in a new tab)
- Navigate Data 360 Segmentationtrailhead.salesforce.com (opens in a new tab)
- Segment Canvashelp.salesforce.com (opens in a new tab)
- Create Filtered Segmentstrailhead.salesforce.com (opens in a new tab)
- Einstein Segmentshelp.salesforce.com (opens in a new tab)
- Why does a red backpack audience need both conditions in one container?
- When does a newly added filter show its count?
- Which attribute type is email opens?
- Why might a custom DMO be missing from Segment On?
The questions are free to read. Answers with their sources and self-grading are included with the pack.
Keep reading with the Data 360 Consultant pack
- Core concepts
- Exam traps
- Worked scenario
The pack includes:
- All 22 lessons of the Data 360 Consultant guide, with reading progress
- Interactive decision walks and step-by-step sequence steppers
- Inline practice questions and one-click topic practice (10 questions for this lesson)
- An official source cited for every claim
- An AI tutor that answers from the guide
- Unlimited timed practice exams