Imagine a customer signs up on your website as "Hers Suri" from "New Delhi." Meanwhile, your CRM already lists them as "Harshit S" from "Delhi." They share the exact same email address, meaning they are the same person. However, because the data is split and slightly conflicting, your system sees two different people.

This is where Identity Resolution comes in. It is a powerful feature within Salesforce Data 360 that merges duplicate records mapped to the Individual Data Model Object into a single, cohesive Unified Individual ID.

To achieve this perfect data harmony, Identity Resolution relies on two critical pillars: Matching Rules and Reconciliation Rules.

Matching rules act as a detective, scanning your data streams to identify which records belong to the same human being. You can leverage two types of matching:

• Exact Match: Looks for identical data, such as the exact same email address or first name ("Hers").

• Fuzzy Match: Catches slight variations or partial data, recognizing that "Suri" and "S", or "New Delhi" and "Delhi", are likely matches.

By combining these (e.g., exact email + fuzzy last name), the system confidently flags the records as duplicates.

2. Reconciliation Rules: Resolving the Conflicts

Once the system groups the duplicate profiles, a new question arises: Which data wins? Should the unified profile say "Delhi" or "New Delhi"? Reconciliation rules resolve these conflicts by defining your preferred values based on three main criteria:

• Most Trusted Source: You can prioritize a specific platform. If your CRM is highly accurate, the system will select the CRM's value ("Delhi").

• Newest Value: The system chooses the most recent data. If the website signup happened today, it will pull the website's value ("New Delhi").

• Most Frequent Value: If the value "Delhi" appears across both a lead and a contact record, but "New Delhi" only appears once on the website, the system picks the most frequent value ("Delhi").

The Audit Trail: Unified Individual Link

Once the heavy lifting is done, how do you track the changes? Salesforce Data 360 provides the Unified Individual Link object. Accessible via the Data Explorer, this object links your new Unified Individual ID back to the original source individual IDs, offering total transparency.

The Bottom Line: Matching rules identify your duplicates, while reconciliation rules solve your data conflicts—giving you a flawless, single source of truth.

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.