Navigating Fragmented and Siloed Customer Data: Is Salesforce Data Cloud The Silver Bullet?

80% of customers expect better customer experiences based on the data the companies collect. But most of the companies struggle with getting the most out of fragmented data accrued by different systems in the organization. To address these data management challenges, Salesforce has just released Salesforce Data Cloud this year. It’s a robust platform that centralizes customer data from multiple sources. It’s built with the power of AI, Data, and CRM. By establishing a single source of truth, it helps businesses to provide outstanding customer experiences in sales, service, marketing, and commerce as well as timely actionable insights.

The Data Cloud Spring ‘24 Release contains new features to boost data usability across the platform services and applications of Salesforce CRM. With the help of features like Data Cloud Triggered Flows and Data Cloud Related Lists, the release makes it possible to view customer engagement data from a website on every customer record in Salesforce.

Using Data Cloud, you can connect data from any source and utilize it within applications that business users depend on for daily operations. This is made feasible since Data Cloud is built on the foundational metadata layer of Salesforce, offering a common language that integrates all Salesforce apps and low-code platform services.

Data Cloud Spring ‘24: Significance and Features

The disconnected data hampers important customers facing tasks like improving customer experience. The powerful combo of data and CRM allows customers to create richer, and more tailored customer experiences. All this data can be connected in real time to Salesforce’s Einstein AI capabilities, which enable generative AI and predictive insights to be fueled by reliable company data.

Key features of Data Cloud Spring ‘24 release include the following:

1. Data Spaces is now GA

Customers can logically separate data, metadata, and processes for departmental, legal, and compliance requirements with Data Spaces.

2. Model Builder is now GA

Depending on the task at hand, customers can build an AI model or select an LLM. For businesses looking to develop their own predictive AI models trained on their Data Cloud data, Model Builder provides a low-code, pro-code, and no-code approach. Customers using Model Builder for generative AI have the option of bringing their own models or selecting from LLMs run by Salesforce.

3. Data Cloud Related Lists is now GA

Data Cloud data can be presented across the Einstein 1 Platform in a Related List on any Salesforce Object by using Data Cloud Related Lists. Now, B2B organizations can utilize real-time interaction data from Data Cloud to instantly enrich their prospects, contacts, and account records.

4. Data Cloud Copy Fields is now GA

Using Data Cloud Copy Fields, customers can expose the insights generated in Data Cloud in core CRM, without requiring complex data integrations and custom development. Customers can now copy data into a field on a Contact or Lead record directly from a Data Model Object or Calculated Insight Object.

5. Data Graphs Improvements

Customers can specify the relationships between data points using Data Cloud’s Data Graphs, doing away with the requirement for manual data join creation or SQL queries. Data Graphs make it easy to guarantee that the right field data is included in an AI application by allowing you to trace related fields and rearrange the relationships. Currently in pilot program, Real-Time Data Graphs enable brands to retrieve and update vital customer data in milliseconds.

6. Data Cloud for Industries Improvements

Customers using Data Cloud for Industries solutions can power industry-specific AI, automation, and workflows using pre-built connectors, data models, calculated insights, and data kits. Financial Services Data Cloud is now GA.

7. Service Intelligence is now GA

Utilizing AI models to forecast “propensity to escalate” and “time to resolve” for their cases based on Data Cloud data, service teams may quickly and easily obtain insights on the service quality through the use of Service Intelligence.

8. Data Cloud Triggered Flows Enhancements

Customers can utilize Data Cloud Triggered Flows to automate business activities when certain conditions are met or when a data point changes across all Data Cloud data sources. Users can now troubleshoot and test their Flows prior to activation.

Conclusion

The Salesforce Data Cloud Spring ’24 Release brings in a new era in data management by completely transforming how companies use and manage their data assets. Businesses can unleash new opportunities, promote innovation, and attain sustainable growth with the help of the Data Cloud’s advanced integration capabilities, AI-powered insights, improved collaboration tools, and powerful security features. With businesses continuing to navigate the complexities of the digital age, Salesforce Data Cloud stands as a beacon of hope, offering a comprehensive solution to their data management needs. The Spring ‘24 release is not merely an update but a transformation in data management, depicting the commitment of Salesforce to empower businesses with innovative solutions that promote success.