In Data Cloud, your data flows from Data Lake Objects (DLOs) into Data Model Objects (DMOs). When dealing with profile data—like Leads from one Salesforce Org and Contacts from another—they all represent the same human being.

To achieve true data unification, Data Cloud uses a core profile DMO called the Individual Object.

• Profile Category Data: Leads, Contacts, and Accounts are mapped here.

• The Goal: Tie different IDs from different systems to a single Individual ID to build a single source of truth.

Syncing Engagement Data from Marketing Cloud

Beyond profile data, you also need to track how customers interact with your brand. This is EngagementData.

By connecting Salesforce Marketing Cloud in Data Cloud Setup, you can deploy Starter Bundles (Email, Mobile Connect, and Mobile Push). This automatically ingests standard data views like clicks, opens, bounces, and subscribers, mapping them instantly into the Data Cloud ecosystem.

Step-by-Step: Mapping Custom Data Extensions

What if you have custom subscriber data inside a Marketing Cloud Data Extension (DE) that isn't part of a standard bundle? You have to map it manually. Here is how:

1. Create a New Data Stream: Select Salesforce Marketing Cloud as the source and locate your specific Business Unit and DE folder.

2. Select the Category & Primary Key: For custom profile data, set the category to Profile and choose your unique identifier (e.g., Subscriber Key) as the Primary Key.

3. Map to Data Model Entities: * Create a Custom DMO to mirror your Data Extension fields.

   • Link and map your Subscriber Key to the Individual DMO (Individual ID) to ensure unification.

   • Map contact details to standard helper DMOs like Contact Point Email, Contact Point Phone, and Contact Point Address.

Once deployed, Data Cloud runs the stream, seamlessly feeding your custom marketing insights into a unified, actionable customer profile!

To start merging your data, you must tell the system which base objects to evaluate.

• Navigate to Identity Resolution and click Create New Rule Set.

• Select the Individual Object as the primary Data Model Object (DMO) you want to unify.

• Define your Rule Set Name (e.g., People) and a unique Rule Set ID.

Once created, the system automatically prepares the target architecture. For every standard object (like contact point email or phone), Data Cloud creates a corresponding unified object, such as Unified Individual and Unified Individual Email.

Step 2: Configure Matching Rules

Next, you define the logic Salesforce uses to catch duplicate records. Because customers rarely provide identical information everywhere, leveraging built-in AI precision rules is essential:

• Fuzzy First Name: Accounts for variations or typos (e.g., matching "Harsh" with "Harshit"). You can adjust the AI precision level to low, medium, or high.

• Exact Last Name: While people play with their first names, surnames usually stay consistent. Setting this to "Exact" keeps your matching accurate.

• Exact Normalized Email: This looks at the core email address, ignoring minor formatting differences.

Data Quality Tip: For normalized matching to work effectively, ensure good data hygiene upfront. Validate customer emails using OTPs or double opt-ins before importing them into Data Cloud.

Step 3: Run and Wait for Reconciliation

After saving your rules, click Update Status. The backend AI will begin processing, running reconciliation rules to link matching IDs across your Salesforce CRM, Marketing Cloud subscriptions, and external data lakes.

Keep in mind that this reconciliation process typically takes 2 to 3 hours to complete. Once finished, you can view the clean, single-source-of-truth profiles in the Data Explorer, fully primed for advanced segmentation and targeted marketing campaigns.

If you’ve ever dug into Salesforce Data Cloud (formerly known as Salesforce CDP / Data 360), you’ve probably run into the Individual object. It sits under the "Profile" category, and honestly, it is the secret sauce to making sense of all your customer data.

But what exactly is it, and why is it so important? Let's break it down in plain English.

The Big Problem: One Person, Many Identities

Imagine a customer named Sarah. Sarah interacts with your business in three different ways:

1. As a Lead: She fills out a form on your website. Salesforce creates a Lead record with a specific Lead ID.

2. As a Contact: Your sales team closes a deal with her. That lead gets converted into a Contact record with a completely new Contact ID.

3. As a Subscriber: She gets synced to Salesforce Marketing Cloud Engagement to receive your newsletters. Now she has a Subscriber ID.

Technically, Sarah has three different identities across your systems.

If you look at your engagement data—like who is opening emails, clicking links, or opening support cases—it’s scattered. To your systems, Sarah looks like three entirely different people.

Enter the "Individual" Object

This is where the Individual Data ModelObject (DMO) comes to the rescue.

In Data Cloud, your data is divided into different categories, like Engagement Data (clicks, opens, visits) and Profile Data (who the person actually is). The Individual object belongs to the Profile category.

Think of the Individual object as a universal bucket. When you bring your leads, contacts, and subscribers into Data Cloud, you don't just leave them in their separate corners. You map all of them to the Individual object.

By pointing all these different profile records to the Individual object, you are telling Data Cloud: "Hey, all of these records represent actual human beings. Keep them here."

How Data Cloud Unifies Your Data

Mapping everything to the Individual object is just step one. The real magic happens with Identity Resolution Rules.

Because you mapped your Leads, Contacts, and Subscribers to the Individual object, you can now write rules to link them together. For example, you can tell the system:

"If a Lead, a Contact, and a Subscriber all share the exact same email address, they are actually the same person."

Data Cloud runs these rules against the Individual object. It matches the duplicates and merges those three separate identities into a single, master profile called the Unified Individual.

Why This Matters

Without the Individual object and identity resolution, your data is siloed. You might send a marketing email to Sarah the "Subscriber" about a product that Sarah the "Contact" already bought.

By unifying everything into a single Unified Individual:

• You get a true 360-degree view of your customer.

• Your marketing becomes smarter because you know exactly who you are talking to.

• You stop wasting effort on duplicate records.

In short, the Individual object is the foundation that allows Salesforce Data Cloud to bridge the gap between fragmented data and a perfect, unified customer experience.

Unlocking a true 360-degree view of your customer requires pulling data from various platforms into one centralized hub. In Salesforce Data Cloud, this architectural journey follows a seamless path from raw source data to a unified profile.

Here is a quick, easy guide to understanding how your data moves through the cloud.

Every source system contains native assets known as DataSourceObjects(DSOs)—think of standard objects like Leads, Contacts, or Accounts. To bring this data into Data Cloud, you must establish a DataStream.

• Starter Bundles: Salesforce provides pre-built bundles for Sales and Service Cloud, allowing you to install and connect standard objects instantly.

• Custom Objects: For unique data sitting outside of standard bundles, you can manually ingest them by selecting the "All Objects" option.

2. Categorizing Your Data

When data streams are configured, the data must be classified into one of three categories. These categories are vital for setting up rules around how data is handled later:

• Profile: Contains Personal Identifiable Information (PII) like names, phone numbers, and addresses.

• Engagement: Tracks real-time or batch behavioral data, such as email opens, link clicks, or website visits.

• Other: Reserved for auxiliary data that does not fit into profile or engagement definitions.

3. From Data Lake Objects (DLO) to Data Model Objects (DMO)

Creating a data stream automatically generates a Data Lake Object (DLO). Think of a DLO as the physical container that holds your raw data.

To make this raw data usable, you must map the DLO to a Data Model Object (DMO) within the standard Customer 360 model. While starter bundles map fields like Contact Point Phone or Contact Point Email automatically, custom data requires manual mapping to organize it correctly.

4. Unifying Profiles with the Individual Object

A single customer might exist as a Lead in one Salesforce org, a Contact in another, and a subscriber in Marketing Cloud. To prevent duplicate profiles, Data Cloud maps all profile data to a core standard DMO called the IndividualObject.

By linking various system IDs to a single Individual ID, Data Cloud resolves identities across multiple connected orgs, creating a singular, unified source of truth for your entire enterprise.

Salesforce Data 360

Imagine running a growing business where your customer data is scattered everywhere. Your website tracks browsing history, your mobile app logs transactions, your CRM manages sales leads, and your marketing tools send out emails and WhatsApp messages.

The major challenge? You cannot see a single customer’s journey in one place. Instead, you are dealing with duplicate profiles across different systems. This duplicate issue weakens your personalization, skews your reporting, and breaks your sales forecasting.

This is exactly where SalesforceData360 (also widely known as DataCloud) comes to the rescue. It acts as a central Customer Data Platform (CDP) that connects, unifies, and activates your data.

The Three Pillars of Data 360

Salesforce Data 360 solves the distributed data crisis through a powerful, three-step process:

1. Connect Internal and External Sources

You don’t need complex coding to bring your data together. Data 360 features inbuiltconnectors for Salesforce apps, Meta ads, Google Ads, Amazon AWS, and Snowflake. It uses datastreams to smoothly pull all this distributed information into a single, centralized data lake.

2. Unify via Identity Resolution

A single customer might have a Meta ID, a CRM Lead ID, and a Marketing Cloud subscriber key, causing them to look like three different people. Data 360 uses IdentityResolution rules—such as matching exact email addresses or fuzzy first names—to clean up the clutter. The result is a single UnifiedProfile where every interaction is tied to one unique ID.

3. Segment and Take Action

With a clean, unified database, you unlock advanced cross-objectsegmentation. You can seamlessly group customers based on combined data from your website, CRM, and marketing history. Finally, use DataActions to instantly trigger a Marketing Cloud journey or a Salesforce Flow to deliver the perfect message at the perfect time.