Data Model Object in Salesforce Data Cloud

Posted on January 20th, 2026 by Sarthak Saxena

DMOs act as a single, clean, and standardized view of customer data by bringing information from different sources into one consistent format. They make sure customer data is accurate, organized, and easy to use, which is why everything else depends on them. Processes like identity resolution, building customer segments, calculating insights, and activating data across channels all rely on well-configured DMOs to work correctly.

A Data Model Object (DMO) is a data structure in Data Cloud representing a unified entity such as:

  • Party / Individual: Unified customer profile combining data from all sources
  • Profile: Extended customer attributes and behavioral data
  • Contact Points: Email, phone, mailing address, social handles, device IDs
  • Engagement: Customer interactions like orders, purchases, website visits
  • Custom DMOs: Organization-specific entities for specialized business needs

Standard vs. Custom DMOs

Standard DMOs provided out-of-the-box by Salesforce:

  • Party (Individual)
  • Profile
  • Contact Point - Email
  • Contact Point - Phone
  • Contact Point - Mailing Address
  • Contact Point - Mobile Device ID
  • Engagement - Order
  • Engagement - Page Visit and many more…

Custom DMOs

Whereas,
Custom DMOs are created for organization-specific data that doesn't fit standard categories

Data Model Relationship Visual Overview:

This page in Salesforce Data Cloud provides a visual overview of Data Model Objects (DMOs) and their relationships, showing how customer data is structured and connected across the system. It represents the unified customer data foundation where core profile objects like Individual and Account are linked with contact points and engagement data. This view helps understand how data from multiple sources comes together to form a single, consistent customer profile that downstream features rely on.

It is mainly used to validate data relationships and dependencies before using the data for business operations. By reviewing this model, teams can ensure identity resolution, segmentation, calculated insights, and activations will work correctly, since all of them depend on these object relationships.

Key points:

  • Shows relationships between Profile, Contact Point, and Engagement DMOs
  • Helps understand how customer identity is unified across objects
  • Acts as a foundation for segments, identity resolution, and activations
  • Useful for impact analysis before modifying or deleting any DMO

Data Model Relationship

**You can open this view by clicking on the list view Icon then Choose Graph option in it.

Mapped Graph

Core DMO Operations

Creating a Data Model Object

Creating a DMO is the foundational step in structuring your unified data model.

When to Create a DMO

  • Standard DMOs don't cover your data requirements
  • You have organization-specific attributes (e.g., loyalty tier, subscription level)
  • You need separate engagement entities beyond standard offerings

Creation Process

Step-by-Step:

  • Navigate to Data Cloud > Data Model in Salesforce Setup
  • Click New button

    Data Model

  • Now a new screen appears in which u can choose as per your need.

    Custom Data Model

  • If you want to modify the existing DMO then choose From Existing otherwise Select New and Click on Next.
  • Now a new page appears to Create a Custom Data Model Object. Now you have to fill up the following fields : Object Label, Object API Name, Object Category and Description.

    Data Model Object

Note :

Object Category tells Salesforce what kind of data the object represents so it can handle profile counting and billing correctly.

Add Field is used to define the attributes (columns) of the object, basically what data you want to store for each record.

Primary Key uniquely identifies each record in the object and is used by Data Cloud to match, update, and prevent duplicate records during data ingestion.

6. Click Save

What Can Be Edited in DMO :

  • Object Label: Change display name
  • Description: Update purpose and usage notes
  • Field Properties: Modify labels and picklist values

Warning: Editing field structure or removing fields may impact dependent segments, identity resolution rules, and activations.

Dependencies on DMO :

  • Segments: Segments that use the DMO for segmentation or filtering
  • Identity Resolution Rules: Rules that match and unify records using DMO fields
  • Calculated Insights: Metrics or derived fields built from DMO data
  • Activations: Campaigns, workflows, or exports using DMO records
  • Segment Membership Objects:: Objects that track segment membership for the DMO

Dependency Flow:

Dependency Flow

Deleting a DMO :

Deletion permanently removes a DMO and all its associated configurations.

Prerequisites for Deletion

Before deletion, you must:

  • Remove all downstream dependencies:

    • Delete any segments using this DMO
    • Remove from identity resolution rules
    • Unlink from calculated insights
    • Remove from activation targets
  • Note: Only custom DMOs can be deleted – Standard DMOs are protected
  • Verify data is no longer needed: for historical analysis or compliance

Best Practices and Implementation

DMO Design Best Practices

  • Leverage Standard DMOs First

    • Use standard DMOs before creating custom ones
    • Standard DMOs follow Salesforce best practices and are optimized
    • Saves implementation time and maintenance effort

Wrong: Create custom "Email_Contact__c" DMO

Right: Use standard Contact_Point_Email DMO

2. Plan for Scale and Performance

  • Consider record volume when designing DMOs
  • Limit fields to essential attributes
  • Use calculated insights for complex aggregations
  • Monitor data cloud credits consumed by operations

3. Document All Configurations

  • Purpose and business rationale for each DMO
  • Field descriptions and data types
  • Data quality expectations
  • Dependent segments and activations
  • Owner and contact information

4. Define Clear Field Naming Conventions

  • Use consistent prefixes (e.g., cust_ for custom, ext_ for external)
  • Use underscores for readability
  • Document naming rules in implementation guide

Good Naming:

  • customer_lifetime_value__c
  • email_opted_out_flag__c
  • Last_purchase_date__c

Poor Naming:

  • CLV (unclear)
  • Opt (too short)
  • lpm (cryptic)

Conclusion

In conclusion, DMOs are the backbone of Salesforce Data Cloud, providing a clean, unified, and reliable structure for customer data. A well-designed DMO ensures accurate identity resolution, meaningful segmentation, and effective activations across channels. Using standard DMOs where possible, carefully designing custom DMOs, and managing dependencies thoughtfully helps maintain data quality, performance, and scalability.

In short, if DMOs are designed right, everything built on top of them works the way it should.

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