If you’ve spent years building Dynamic Lists and Engagement Studio programs, opening Data 360 for the first time can feel overwhelming. Unified Individuals, Segments, Calculated Insights, Data Spaces; it looks like a whole new world. But here’s the thing: it’s not.
At its core, segmentation hasn’t changed. You’re still trying to get the right message to the right person at the right time. What has changed is how much data you have to work with. Instead of building audiences from Prospect records and email engagement alone, Data 360 lets you layer in website activity, CRM data, opportunity history, subscription preferences, and more.
Here’s how to bridge what you already know with what you’ll find in Data 360.
The Biggest Mindset Shift: From Lists to Audiences
In Account Engagement, everything starts with a list.
Need a webinar audience? Build a list.
Need a re-engagement campaign? Build a list.
Need a nurture track? Build a list.
In Data 360, you build reusable audience definitions instead. One segment can power multiple campaigns, journeys, and channels. You’re not creating a new list for every initiative. Think of it this way:
Account Engagement: Campaign → Build List → Send Message
Data 360: Define Audience → Activate Anywhere
The shift from campaign-specific lists to reusable audiences is the most important concept to internalize before you start building.
Terminology Translation
Before you build anything, here’s the cheat sheet:
Account EngagementData 360 What It MeansProspectUnified IndividualThe person you’re marketing toDynamic ListSegmentA reusable audience built from defined criteriaDynamic List RulesSegment CriteriaThe logic used to determine audience membershipList MemberSegment MemberSomeone who qualifies for the audienceProspect ActivityEngagement DataBehavioral data used for targetingMarketing ListPublished SegmentA ready-to-use audience for activationScore & GradeAttributesSignals used to identify high-intent audiences
Once that mapping clicks, the platform becomes a lot less intimidating.
Before You Build: Know Your Data
One thing that surprises most Account Engagement users is how much data is available in Data 360. Depending on your setup, you may have access to:
Prospect data
CRM data
Email engagement
Forms
Landing Pages
Website activity
Preference center subscriptions
Opportunity data
External data sources
This is where Data 360 starts to shine.
In Account Engagement, we ask: “Who opened my email in the last 30 days?”
In Data 360, we ask: “Who opened my email in the last 30 days, visited my pricing page, and doesn’t currently have an open opportunity?”
That’s a fundamentally more sophisticated audience, and it’s exactly why organizations are investing in Data 360.
One important caveat: Not every org has the same data sources connected. Before building complex segments, take time to understand what’s actually flowing into Data 360 and how frequently it refreshes. Knowing your data inventory upfront will save you a lot of troubleshooting later.
Building Your First Segment
Navigate to Data Cloud > Segments and select New. You’ll see four segment types:
Standard Segments are your go-to. These are the closest equivalents to Account Engagement Dynamic Lists and support the vast majority of marketing use cases. Start here.
Waterfall Segments let you prioritize audiences and prevent contacts from qualifying for multiple competing campaigns simultaneously — useful when running multiple offers at once.
Real-Time Segments evaluate audiences on demand for use cases requiring immediate qualification. Powerful, but they come with limitations.
Once you’ve selected Standard Segment, there are four ways to build your audience.
Option 1: Use the Visual Builder
The Visual Builder offers the most flexibility and is where most marketers spend the majority of their time. The process is straightforward:
Create a New Segment
Select your Data Space (most often your Default Data Space)
Choose the object you want to segment on (most often Unified Individual)
Name your Segment
Configure your publishing settings
Drag attributes onto the canvas and define your criteria
Save and publish
Understanding Direct Attributes vs. Related Attributes
This is one of the biggest mindset shifts for Account Engagement users.
When building criteria in the Visual Builder, you’ll typically see two types of attributes:
Direct Attributes
Direct Attributes live directly on the object you’re segmenting against.
For example, if you’re building a segment on the Unified Individual object, direct attributes might include:
First Name
Last Name
Country
State
Preferred Language
Think of these as fields that belong directly to the person.
Example: Country = United States
This is a simple, direct attribute filter.
Related Attributes
Related Attributes come from connected objects that are related to the object you’re segmenting on.
Examples include:
Email engagement activity
Opportunities
Campaign Membership
Website activity
Orders
Cases
Think of these as records associated with the person rather than fields that live directly on the person.
Example: Opened an email in the last 30 days
The email open isn’t stored directly on the Unified Individual record. It’s stored on a related engagement object.
When Should You Use Each?
A simple rule:
Use Direct Attributes when filtering on profile or demographic information.
Use Related Attributes when filtering on behavior, engagement, transactions, or relationships.
If you’re asking “Who is this person?” you’re usually looking at Direct Attributes.
If you’re asking “What has this person done?” you’re usually looking at Related Attributes.
Understanding that distinction makes segment building much easier and helps explain why some criteria appear in different areas of the builder.
Option 2: Use Quick Filters
Need a common audience fast? Quick Filters offer predefined criteria for standard scenarios like:
New Contacts created today
New Leads created today
Recent Campaign Members
Contacts related to a won Opportunity
Access Quick Filters by navigating to Campaign while in the Marketing Cloud Next app. Open a campaign and select Select Segment. It’s a great starting point if you’re brand new to the platform.
Option 3: Use Einstein to Build a Draft
Not sure where to begin? Einstein Segment Creation lets you describe the audience you want in plain language:
Show me subscribers who opened an email in the last 30 days, visited our pricing page, and are subscribed to product updates.
Einstein generates a draft segment you can review, refine, and publish. Think of it as a shortcut to a first draft and always validate the output before going live.
Option 4: Use a Dynamic Segment
If you find yourself creating the same types of audiences repeatedly, Dynamic Builders can help streamline the process. Instead of starting from scratch each time, Dynamic Builders let you create reusable audience templates with configurable criteria. Marketers can then generate new segments from those templates by simply selecting or updating a few values, helping ensure consistency across campaigns while reducing manual effort. They’re especially useful for organizations with standardized audience definitions or recurring segmentation needs, allowing teams to scale segmentation without rebuilding the same logic over and over.
Which option should you choose? If you’re just getting started, use Quick Filters for common audiences or the Visual Builder for custom logic. Einstein Segment Creation is a great way to generate a first draft from natural language, while Dynamic Builders are best when your organization wants to standardize and reuse the same audience patterns across multiple campaigns.
Tips, Gotchas, and Things I Tell Every Client
Use the IN Operator Instead of Stacking OR Conditions
If your CRM has multiple versions of the same value, the IN operator saves you a lot of time. Instead of building three separate OR conditions, write:
Country IN (USA, US, United States)
It supports up to 100 values. Clean, readable, and much easier to maintain.
Understand Measurements, Operators, and Values
When working with behavioral data, Data 360 often asks you to combine three pieces:
Measurement
Operator
Value
For example: Email Opens → Count → At Least → 1
This translates to: “The person has opened at least one email.”
Another example: Email Clicks → Count → Greater Than → 5
This translates to: “The person has clicked more than five emails.”
Think of it like a sentence: Measurement + Operator + Value = Audience Rule
Examples:
Count At Least 1
Count Equals 0
Sum Greater Than 1000
Count Between 5 and 10
If a segment returns unexpected results, this combination is often the first place I investigate. The measurement may be correct, but the operator or value may not align with the business requirement.
Use Include and Exclude Intentionally
One of the most common mistakes I see is placing all data requirements into the “Include” section. Instead, think of Include as those who belong and Exclude as those who don’t belong. Separating those concepts creates cleaner segments and makes troubleshooting much easier.
Include Criteria: Country IN (USA, US, United States)
Exclude Criteria: Emailed in the last 3 days
Use EQUALS When Your Data Is Clean
When a field is standardized, and you only need one exact match, EQUALS is the right call. Country EQUALS USA will only return records where the value is exactly “USA.” No flexibility, but that’s the point.
Build Frequency and Recency Into Your Logic
This is where Data 360 starts to feel genuinely different from Account Engagement. You can filter by:
Has been emailed X times in the last Y days is great for suppression. If someone has received 3 emails in the last 7 days, you probably don’t want to send them a fourth.
Has not engaged in X days is your re-engagement and deliverability workhorse. Use it to identify lapsed subscribers before they become a problem.
Subscribed to [Preference] will build audiences based on what contacts have explicitly opted into. Increasingly important for compliance and deliverability.
Always Preview Before You Publish
Segment Preview lets you check audience size, sample records, and whether your include/exclude logic is working as intended. A few minutes here can save hours of troubleshooting later.
Account for Processing Time
Data 360 isn’t always instantaneous. Initial data ingestion can take days, depending on volume. Segment calculations take time and Dynamic Lists connected to a Data 360 Segment can take up to three hours to populate the first time. If nothing shows up immediately, give it time before assuming something is broken.
Not All Account Engagement Activity Is Automatically Available
A common misconception: not every historical activity flows into Data 360 by default. What’s available depends on your connector configuration and the Filter By Date you set when connecting. Before building complex engagement-based segments, confirm what data is actually being ingested.
Data 360 Doesn’t Honor CRM Visibility Rules
This one surprises many Salesforce Admins. Users can segment records in Data 360 that they can’t see in the CRM. If access control matters for your org, address it before rolling out segmentation broadly. The most reliable controls are user permissions and Business Units.
From Segment to Activation
One of the biggest misconceptions I encounter: adopting Data 360 means abandoning Account Engagement. It doesn’t. One of my favorite use cases is building sophisticated audiences in Data 360 and activating them directly through Account Engagement via the Data 360 Connector. To connect a Data 360 Segment to Account Engagement:
Navigate to Account Engagement → Segmentation → Lists
Create a Dynamic List
Select Data Cloud Segment as the Dynamic List Type
Choose your published segment
The first sync takes up to three hours. After that, membership updates automatically whenever the segment refreshes. Once connected, the Dynamic List works anywhere in Account Engagement, including Engagement Studio, Automation Rules, List Emails, Completion Actions, and Reporting. Data 360 identifies the audience. Account Engagement engages it. That’s where the value compounds.
Three Segments to Build First
Not sure where to start? These three are worth building in almost every org.
Recently Engaged Contacts: people actively interacting with your brand. Use for webinar invitations, product launches, or newsletters.
Opened an email in the last 30 days, OR
Clicked an email in the last 30 days, OR
Visited your website in the last 30 days
Inactive Subscribers (90+ Days): Subscribers who’ve gone quiet. Use for re-engagement campaigns, deliverability cleanup, or preference center outreach. This audience frequently surfaces new pipeline.
Opted in, AND
No opens in 90 days, OR
No clicks in 90 days
Preference Center Subscribers: Contacts who’ve told you exactly what they want. Use for targeted newsletters, product announcements, or event promotions.
Opt in to Product Updates
Data 360 segmentation isn’t replacing the skills you’ve built in Account Engagement; it’s extending them. You’re still defining criteria, building audiences, and activating campaigns. The difference is you now have richer data and more ways to use it. Start simple. Build a Quick Filter segment, get comfortable with the interface, then move into the Visual Builder. Before long, you’ll stop asking how to recreate Dynamic Lists and start asking what was possible all along.
Original article: Segmenting in Data 360 for Account Engagement Users
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