Ultimate Guide to Identity Resolution in Salesforce Data Cloud

What is Identity Resolution in Salesforce Data Cloud?

In Salesforce Data Cloud, identity resolution is the intelligent process of matching and merging disconnected customer interactions from various sources into an actionable, single, and unified customer profile. 

Simply put, when a customer interacts with your brand across multiple touchpoints (website, mobile app, emails, social media engagement, and in-store purchase), identity resolution stitches these interactions together to create a single, cohesive view of each customer. Without it, customer data remains siloed, limiting businesses’ ability to deliver personalized experiences. 

Why Identity Resolution is Important for Modern Businesses?

Most businesses encounter a similar problem of fragmented customer data, leading to inconsistent and inefficient customer experiences. Studies like Shep Hyken’s customer service and CX research in 2025 indicate, “84% of customers prefer companies that offer personalized customer experiences. This is also true for Gen Z, who values personalization above all else.

Identity resolution in Salesforce Data Cloud is the foundation for delivering this kind of experience, empowering businesses to meet and exceed customer expectations.

How Does Identity Resolution in Salesforce Data Cloud Work? Step-by-Step Breakdown

Step 1: Comprehensive Data Collection 

Data Cloud ingests data from diverse sources (online and offline), including marketing automation, CRM, and e-commerce platforms. 

Step 2: Match and Merge the Profiles

The Data Cloud utilizes four matching rules for data deduplication. 

• Deterministic Matching: It is a primary method used by Salesforce Data Cloud, which scans through exact matches using unique identifiers (email, phone, CRM ID).

For example, shane@xyz.com in Salesforce Sales account = shane@xyz.com (account on Salesforce Marketing Cloud), 100% match.

• Probabilistic Matching: It refers to an educated guess (not exactly a 100% match), through analyzing patterns (name variations, locations, and devices). For example, Jack S (NY) + J Smith (New York) + Same Device is likely to be the same person. 

It is used for anonymous users (website visitors or ad clicks) and governed by consolidation rates. Customer data with duplicate profiles is expected to have higher consolidation rates (like >75%) than with unique profiles.  

• Machine Learning: It is an AI-powered identity resolution that improves matching over time by learning patterns. It uses reconciliation rules to define how to select a single value. 

For example, if a unified profile is created with multiple sources that include different data about the customer’s first name. In one source name is Kristian, and Kris in the second source. If the rule for the field’s latest updated name and Kris has been modified recently, then, the reconciled value is Kris that is used for segmentation and data activation. 

• Graph Database: Maps relationships between data pointers (devices, emails, IPs) to speed up matching across fragmented data. 

For example, link Jack’s Mobile + Laptop + Home Address with the identity graph. 

Identity resolution in Data Cloud combines them, but first, it uses deterministic matching to find exact records. If there are no exact matches, then it uses probabilistic and graph DB for similar devices and similar names, and ML refines rules over time.

Step 3: Creating the Golden profile

After combining all interaction data (like support tickets, emails, and purchases) into a golden record, the result is a continuously updated master profile including: 

• All verified identifiers (email, devices, and loyalty numbers)
• Complete interaction history (purchases, service cases)
• Behavioral insights (preferences and engagement patterns)

Step 4: Activating the Data

By activating the golden data, it helps the different teams:

• Marketing: Help marketing teams send personalized emails to individuals once (not duplicates), leading to higher conversion rates.
• Sales: Sales teams can reduce the sales cycle by having complete context, eliminating the scope of reps wasting time researching “new leads” who are existing customers. 
• Service: Faster resolutions with automatic caller recognition, so agents do not have to ask for basic information from customers.

Real-World Example on How Data Cloud Identity Resolution Helped Businesses?

Challenges: Our client, a leading US-based ecommerce clothing company, struggled with siloed customer data across platforms such as website, mobile, and CRM. It led to: 

• Inconsistent marketing campaigns: As the client’s data spread across different channels, their marketing team was unable to understand customer behaviours and send promotional messages that didn’t connect with the audience. 
• Missed sales opportunities: Lack of reliable information hindered the customer identification process, resulting in wasted efforts on those customers who were likely to leave. 
• Rising cart abandonment rates: Our client was struggling with the increasing cart abandonment rates due to a lack of personalization and insufficient follow-up strategies.  

Solution: By understanding the challenges, our experts implemented Data Cloud and integrated it with their systems. It led:

• Unified fragmented data into 360-degree customer profiles (with Identity resolution). 
• Enable hyper-personalized campaigns using real-time behavioral insights.

Read the Full Case Study: From Solutions Insights to Results

Key Benefits of Identity Resolution: Why Does Your Business Need It?

Identity resolution in Data Cloud unlocks revenue opportunities hidden in the disconnected customer interactions. Here’s how it benefits organizations:

No More Duplicate Profiles 

With identity resolution in the Data Cloud, you can merge multiple records and receive a single (master) record for each individual, preventing the issue of sending a promo code to the same person multiple times. This enables you to stop wasting marketing money on duplicate communications.   

Personalized Marketing 

By developing a golden profile of each individual, you can tailor messages based on a complete customer history and provide recommendations through the most suitable channels. 

For example, “Here are compatible accessories based on your recent laptop purchase.” 

Better Sales and Support

Understand the customer before making a call, as it helps the sales team determine whether they are reaching out to a prospect, lead, or existing customer. Also, service agents get instant access to the complete customer context when a customer calls.  

Data Compliance

Maintain clean and secure data through the robust security features of the Salesforce platform. You can effortlessly maintain compliance with industry standards and regulations. 

For example, identity resolution automatically deletes outdated records as per GDPR, so you do not have to worry about compliance.

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Conclusion

Salesforce Data Cloud’s identity resolution transforms fragmented data into actionable customer insights. In an era where increasing customers expect personalized support and services from brands, this capability of Data Cloud empowers businesses to cater to every interaction and accelerates operational efficiency. 
If you want to successfully implement, we at Cyntexa offer you Salesforce Data and AI experts. We will help you throughout the implementation of Data Cloud and deliver a better customer experience and satisfaction.

AUTHOR

Vishwajeet Srivastava

Salesforce Data Cloud, AI Products, ServiceNow, Product Engineering

Co-founder and CTO at Cyntexa also known as “VJ”. With 10+ years of experience and 22+ Salesforce certifications, he’s a seasoned expert in Salesforce Data Cloud & AI Products, Product Engineering, AWS, Google Cloud Platform, ServiceNow, and Managed Services. Known for blending strategic thinking with hands-on expertise, VJ is passionate about building scalable solutions that drive innovation, operational efficiency, and enterprise-wide transformation.