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Identity Resolution Matching & Reconciliation Rules In Data 360 | Peoplewoo Skills

Fri, 10 Jul 2026 10:54:17 +0530

Identity Resolution Matching In Salesforce Data 360

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.

1. Matching Rules: Finding the Duplicates

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.

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Explore Salesforce Data 360 (Data Cloud)

Learn Salesforce Data 360 with real-world ingestion, identity resolution, segmentation, and activation workflows. Build job-ready Data Cloud consulting skills with hands-on practice and interview-focused preparation.

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Integrating Salesforce Marketing Cloud Engagement With Data 360 | Peoplewoo Skills

Thu, 09 Jul 2026 15:01:27 +0530

Introduction

Imagine having customer data scattered across multiple Salesforce Orgs, Marketing Cloud, and external systems. How do you bring it all together? That is where Salesforce Data Cloud shines.

Data Cloud allows you to stream data from various sources and map them to a single, unified view. Let’s break down how this works—from standard starter bundles to mapping your custom data.

The Power of the "Individual" Object

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:

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

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What Is Salesforce Data 360(Data Cloud)? | Peoplewoo Skills

Thu, 25 Jun 2026 13:29:34 +0530

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.

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Data Streams, DLO & DMO in Data 360 | Peoplewoo Skills

Fri, 26 Sep 2025 15:27:25 +0530

How Salesforce Data Cloud Works

A simple breakdown of how data moves from isolated systems into a single, unified view.

Connecting the Source: DSOs and Data Streams

Before Data Cloud can harmonize your data, it requires a secure ingestion pipeline to your external environments.

Data Source Objects (DSOs): These are the native objects residing inside your source systems—such as the Lead, Contact, or Account objects within Salesforce Sales Cloud.
Data Streams: The actual functional connections established to transition data from your DSOs into Data Cloud. Data Streams seamlessly support both real-time integrations and batch uploads.

To accelerate implementation, Salesforce offers pre-built Starter Bundles (e.g., Sales Cloud and Service Cloud bundles). Deploying these bundles automates the connection setup for standard enterprise objects, removing the need for manual configuration.

Data Categorization: Profile vs. Engagement

When connecting custom objects or external data lakes, Data Cloud requires you to categorize the incoming data schema. This taxonomy determines how data behaves during identity resolution workflows.

Category	Definition	Enterprise Examples
Profile	Personally Identifiable Information (PII) defining who the customer is.	Leads, Contacts, Accounts (Names, Emails, Addresses)
Engagement	Behavioral tracking data detailing actions taken by the customer.	Email opens, link clicks, website visits, form downloads
Other	Supplementary data that does not strictly match Profile or Engagement schemas.	Product catalogs, support cases, operational logs

The Architecture: DLOs vs. DMOs

The journey from raw data ingestion to standard data modeling relies on two foundational architecture components:

1. Source System / DSO (Raw Source)
↓ Connected via Data Stream
2. Data Lake Object / DLO (Physical Storage Container)
↓ Standardized via Data Mapping
3. Data Model Object / DMO (Unified Customer 360 Shape)

Creating a Data Stream automatically provisions a corresponding Data Lake Object (DLO). The DLO serves as the exact physical storage container for your raw data inside Data Cloud. However, at this stage, the data is unstructured and unaligned with the broader ecosystem.

To make this information usable, fields from the DLO must be mapped directly to a Data Model Object (DMO). DMOs are the standard semantic templates that comprise the global Customer 360 model.

4. The Foundation of Unification: The Individual Object

The single most critical DMO for true profile unification is the Individual object.

In complex multi-org enterprise environments, a single human being often exists under completely different unique keys across multiple systems. They might be tracked as a Lead ID in Sales Cloud, a converted Contact ID in a secondary business unit, and a Subscriber Key within Marketing Cloud.

By mapping every single profile-category data stream to the central Individual Object, you establish a universal anchor point. This mapping enables Data Cloud's Identity Resolution engines to successfully cross-reference disparate source records and consolidate them into one single, cohesive, and actionable customer profile.

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