In other parts of this series, we discuss some of the other tools Salesforce has introduced to help you harness AI for your business and CRM. Features like Prompt Builder allow you to build reusable templates for your users to interact with Large Language Models (LLMs), the technology behind generative AI, at scale and with consistency. Agentforce allows you to increase efficiency in sales, service, marketing, and more through autonomous or semi-autonomous AI agents. And the Einstein Trust Layer gives you peace of mind that your customer data is secure as you leverage LLMs for AI-enabled workflows. We cover these topics in more detail in their own articles, but where does Data Cloud fit into all this?
Well, it fits everywhere! While Data Cloud isn’t a prerequisite to using any of the other features we mentioned, it is an amplifier. Data is the lifeblood of any effective AI solution. With more data, your AI can deliver more comprehensive insights, and facilitates more accurate, consistent, and personalized customer interactions. Through Data Cloud, you unlock the potential of your enterprise data across all your systems to leverage AI with exponentially greater effectiveness.
Data Cloud is an incredibly comprehensive and dense subject; in fact there is an entire certification course and 20+ hours of modules covering it in Trailhead alone. In this article, we’ll cover a high-level overview of what Data Cloud is, how it works, and how it supports your AI solutions.
What is Data Cloud?
Salesforce Data Cloud is an end-to-end platform that enables businesses to unify data from various sources—structured and unstructured—into a single, actionable view. Structured data typically includes Salesforce records such as customer accounts, leads, or service cases. This data is clean, organized, and fits neatly into predefined fields and tables. Unstructured data, on the other hand, includes complex data types like call transcripts, emails, PDFs, and social media posts.
Data Cloud stores large-scale, raw data in Data Lake Objects (DLOs), enabling businesses to gather a comprehensive picture of customer behaviors, interactions, and preferences. This data is then mapped to Data Model Objects (DMOs), where it is structured and unified to allow companies to deliver more insightful, personalized, and effective AI-driven customer interactions across Salesforce solutions.
Unified Profiles: A Holistic View of Your Customer Data
One of the hallmark features of Data Cloud is the creation of Unified Profiles, a holistic representation of each customer. Unlike a “golden record” approach in master data management (MDM) solutions, which overwrites data to select a “best” value (e.g., the most accurate email or phone number), Data Cloud retains all data points with full traceability. This “bucket” model captures multiple data points and identifies their sources, allowing businesses to access the full history of customer details across systems. Unified Profiles thus provide a transparent, reliable view of each customer’s journey, enabling a level of personalization and precision not easily achieved with other data management approaches.
How Data Cloud Works
Data Cloud’s functionality centers around three core pillars—Connect, Harmonize, and Activate—which together form a cycle of data integration, organization, and application.
Connect your Data: Ingestion, Modeling, and Mapping in Data Cloud
Connecting your data is a prerequisite to leveraging Data Cloud. Through ingestion, Data Cloud collects data from a variety of sources including your CRM, external databases, and storage solutions like Amazon S3. This is also useful for businesses utilizing multiple Salesforce systems like Sales Cloud or Account Engagement (formerly Pardot). Once ingested, this raw data is stored in Data Lake Objects (DLOs).
From here, Data Model Objects (DMOs) transform and standardize that raw data into a structured format suitable for Salesforce applications. Unlike traditional Salesforce objects that hold all data within a single record, Data Cloud breaks down complex data into more granular DMOs. For example, in your Salesforce org, information like “address” or “email” are stored as fields on a Lead record, but in Data Cloud this contact information into objects like Contact Point Address for addresses and Contact Point Email for email details. This flexibility enables businesses to map data from disparate sources into a standardized, cohesive framework.
Harmonize your Data: Unify Data using Identity Resolution
Data Cloud’s unification capabilities revolve around Identity Resolution, which consolidates fragmented data to create comprehensive customer profiles. This process is especially critical for businesses managing data from multiple systems.
Identity Resolution employs Match Rules and Reconciliation Rules to connect and refine data points across platforms. Match Rules determine how data points—such as email addresses or phone numbers—are linked, using methods like Exact Matching (for identical matches), Fuzzy Matching (for slight spelling variations), and Normalization (for formatting differences). Reconciliation Rules then dictate which data to display in the unified profile, based on logic such as the most recent update or most frequently occurring value.
Ultimately, a unified profile serves as the accessible “face” of a vast network of underlying data stored in Data Cloud, distilling complex, cross-platform information into a holistic, manageable view for your users.
Activate your Data: Calculated Insights, Segmentation, and Leverage AI
Once data is connected and harmonized, Data Cloud enables companies to activate this data in ways that directly drive customer engagement. Calculated Insights and Segmentation are two methods by which Data Cloud organizes and applies customer data for precise, targeted outreach.
Calculated Insights allow you to define metrics, like customer lifetime value or engagement scores, which can dynamically update and refine segments over time. Marketers can use these insights to build segments based on customers’ purchasing behavior or interaction history, leveraging the Segment Canvas Interface to create, filter, and organize them into actionable groups for personalized marketing campaigns or tailored customer service.
Data Cloud also enhances other AI-enabled Salesforce tools, including Prompt Builder and Agentforce, by providing an audit trail and more data-driven insights. For example, Prompt Builder can use Data Cloud’s Unified Profiles to dynamically ground responses in the customer’s most relevant data, while Agentforce agents benefit from having up-to-date customer profiles and insights directly accessible, improving the relevance of each interaction.
Final Thoughts
Salesforce Data Cloud serves as the backbone of AI-driven customer experiences, transforming varying data into unified profiles that fuel intelligent, personalized interactions. Through its Connect, Harmonize, and Activate pillars, Data Cloud integrates and organizes data from across your business systems, creating a comprehensive foundation for AI and automation within Salesforce. This infrastructure not only supports high-level segmentation and calculated insights but also amplifies the impact of tools like Prompt Builder and Agentforce.
If your business is ready to maximize its data potential, our team at Port & Starboard can help you integrate Salesforce Data Cloud for a more cohesive, AI-enhanced approach to customer engagement. Reach out to us today to learn how Data Cloud and other Salesforce solutions can transform your data into a powerful asset for growth.
