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.