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.

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.

After the automated backend process finishes, head over to the AppLauncher (the nine-dot icon). Search for DataCloud and open it.

Thanks to your new permission set, the entire dashboard is now unlocked. You will see all configuration and menu items fully enabled, meaning you are officially ready to start connecting data streams and building out your Data 360 strategy!

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.

First, let’s navigate to the workspace and lay the groundwork:

1. Click the AppLauncher and search for AgentforceStudio.

2. Click PromptTemplates to open the Prompt Builder in Setup.

3. Select NewPromptTemplate and fill out the details:

   • Prompt Template Type: Field Generation

   • Prompt Template Name: quick summary

   • Template Description: A short summary of case details.

   • Object: Case

   • Object Field: quick summary

Click Next, and you’re ready to start building.

Step 2: Add Instructions & Dynamic Merge Fields

Next, ensure OpenAI GPT4 Omni Mini is selected as your model. Paste the following instruction text into the prompt box:

"Summarize the concatenation of the contents of the comment bodies of comments along with the text from subject, the case priority, which is priority, and the case type, which is type. Keep the response to a single short paragraph."

To make this template dynamic, we need to replace those ALL-CAPS placeholders with actual Salesforce data. Use the InsertResource button to swap them out:

• Priority: Place your cursor before "priority," click Insert Resource > Case > Priority, and delete the old placeholder word.

• Comments: Replace "comments" by selecting Case > Case Comments.

• Type: Replace "type" by selecting Case > Case Type.

• Subject: Replace "subject" by selecting Case > Subject.

Your placeholders will turn into clean, blue merge fields.

Step 3: Test and Activate

Before launching it to your users, let's make sure it works perfectly:

• Click Save.

• Click Preview, then expand the Inputs box.

• Find and select a sample record, like Case 00002.

• Click Preview again to see the LLM generate a concise case summary in real-time.

• Once it looks good, click Activate.

And just like that, you've successfully automated your case summaries. Less time skimming logs, more time solving problems!

A Subscriber is an individual who has actively opted in to receive communications from your company via a specific channel.

• EmailStudio: Opting into emails makes someone an Email Subscriber, adding them to the "All Subscribers" list.
• MobileStudio: Opting into SMS or push notifications makes them a Push/SMS Subscriber.

Subscribers are inherently siloed by the specific channel they use to interact with your brand.

What is a Contact?

Businesses need a single, holistic view of a customer's entire footprint. That’s where Contacts come in.

Inside ContactBuilder, the AllContacts section acts as your master database. Marketing Cloud treats an individual as a single contact, regardless of how many channels they use. Whether you receive an email, an SMS, or a push notification, SFMC ties all of these channel addresses and activities back to one unique Contact.

TheGoldenRule: A contact can exist without being an email subscriber. For instance, if someone only signs up for mobile push notifications, they will exist in All Contacts (with their App ID) but will be completely absent from Email Studio's All Subscribers list.

Key Differences at a Glance

How is Contact Data Created?

Contacts enter your "All Contacts" database through several primary methods:

• DirectImports: Loading data straight into Contact Builder.
• MarketingSends: Sending a communication to a new List or Data Extension automatically registers them.
• SalesforceDataSync: Syncing data seamlessly from Sales or Service Cloud.
• APIs: Creating contacts programmatically from external systems.

By understanding this distinction, you can better manage your cross-channel journeys and ensure your audience gets a unified experience, no matter the channel.