With the introduction of Einstein and Data Cloud, Salesforce is revolutionizing application development, creating the most significant shift and opportunities for developers in decades. But what exactly is Data Cloud, and how does it complement services powered by Einstein? Let’s answer this from a developer’s point of view.

Salesforce provides a suite of services and tools that provide capabilities to acquire, develop, and build loyalty with customers, employees, and partners. These services and tools are called Salesforce Customer 360.

For developers, the challenge is to provide data at scale to power predictive models and ground prompts to get accurate responses from their large language models, and do it securely.

Let’s take a look at how Data Cloud and Salesforce AI fit into Salesforce Customer 360 since these products underpin data and AI at Salesforce.

The foundation for data + AI

The foundation of Salesforce Customer 360 is Data Cloud + AI + MuleSoft. These services address the fundamental challenge of getting access to data at scale, and applying AI to provide proactive insights.

The foundation of Salesforce Customer 360

Understanding AI at Salesforce

Einstein is an umbrella term for the features and capabilities of Salesforce that use machine learning, deep learning, natural language processing, and generative pre-trained transformers (GPT) to model data to provide proactive insights. This layer allows developers to use existing investments in predictive models and large language models (LLMs). It also provides developers with access to models that Salesforce manages, removing the barrier for those customers who aren’t ready to build their own.

The importance of data in your AI strategy

Getting access to your enterprise data is key for AI models. Data Cloud ingests data from Salesforce applications and your enterprise applications. At its heart, Data Cloud is a hyperscale data platform — like a data lakehouse. Unlike other data lakehouses, Data Cloud is uniquely positioned to provide the foundation for applying AI insights to your data and then putting that data in the hands of your customers and front-line staff.

Unlock enterprise data with MuleSoft

Connecting to data sources that power your AI strategy requires integrating and securing their data assets. MuleSoft provides connectors to unlock data silos and a governance layer to securely ingest data from common systems. Implement REST, SOAP, and event-driven API designs, enable business teams to connect apps easily with MuleSoft Composer, and eliminate manual tasks with robotic process automations.

The user experience for Data + AI

If Data Cloud + AI + MuleSoft is the foundation of Salesforce Customer 360, then the user experience layer comes from market-leading applications across sales, service, marketing, commerce, and analytics.

Applications in Salesforce Customer 360

Data and AI alone aren’t useful unless you can use the insights to drive an outcome that makes a difference to your business. Segmenting customers on predictive insights to provide better marketing campaign engagement, or creating a case as soon as an issue arises in a device installed in your customer base, drives efficiency improvements that make a material difference to your company.

Bringing the two halves of Salesforce Customer 360 together gives a holistic picture showing how Data + AI + MuleSoft underpins Salesforce Customer 360.

A high-level overview of how Data + AI + MuleSoft underpins applications in Salesforce Customer 360

This picture shows how Data Cloud and Einstein provide a foundation that delivers insights to your business. For example, Einstein gets engagement history data from Marketing Cloud campaigns to determine the best time to send emails, which then becomes available to Marketing Cloud Journey Builder as Send Time Optimizations. For commerce use cases, Einstein can receive purchase history and provide your digital storefront with the next best offer. For Data Cloud, Einstein Studio is the hub for predictive models that can be applied across your ingested data sources.

Data Cloud provides new capabilities to take action on data changes anywhere in a company’s enterprise. Data ingested and mapped to a unified profile becomes available to admins and developers.

There are many examples of how you can use these technologies, but let’s take a look at three specific examples to help highlight Data + AI working together.

1) Access data in Data Cloud with copy field enrichments

Data Cloud can supply your CRM applications with insights that help drive business outcomes. Calculated insights in Data Cloud can operate at scale across multiple sources of enterprise data. Consider the ability to calculate the lifetime value of your customers, identify donors who donated last year but not this year, or know which customers are most engaged with your brand. Having this information in the hands of the Sales, Service, and Marketing teams is invaluable.

Copy field enrichments replicate this key data into your CRM applications using the Contact, Account, or Lead objects. This allows you to then use the values to drive your CRM reports and dashboards, and contribute to processes on the platform like Flow Builder without having to call out to Data Cloud.

Data Cloud with copy field enrichments

Object Manager lets you set up the copy field enrichment, allowing you to specify a Calculated Insights object or object related to an Individual DMO. You can then map fields in the Data Cloud schema to Salesforce. Once saved, a request is made to synchronize the fields specified to the object in Salesforce using the Bulk API. The first sync is a full sync followed by incremental syncs triggered by any changes in Data Cloud data for the fields you’re copying.

Copy field enrichments replicate key fields from Data Cloud to make them available in your CRM applications.

2) Improve accuracy and relevancy in AI responses using Data Cloud and Prompt Builder

Data Cloud with Prompt Builder

You can create prompt templates using your Salesforce data and provide logic with Apex and Flow Builder. Einstein provides the trusted layer to access LLMs. Data Cloud provides additional capabilities:

  • Link custom large language models using OpenAI and Azure Open AI to use in Prompt Builder
  • Query your structured data ingested from your enterprise
  • Search unstructured data sources using semantic search (Pilot)

Data Cloud supplies Prompt Builder with data that can improve the accuracy and relevancy of responses.

3) Use predictive insights in Data Cloud to drive effective marketing campaigns

Data Cloud enables companies to use AI in the form of predictive modeling. This can be point-and-click modeling with the help of Einstein, or custom modeling using tools like Google Vertex AI and Amazon SageMaker. Predicting outcomes based on previous data is a powerful feature that helps Sales, Service, Marketing, and Operations teams.

Data Cloud with Marketing Cloud

In the diagram above, Data Cloud is using an endpoint exposed from Google Vertex AI. It then uses the model to make predictions based on data flowing into Data Cloud. These predictions, together with the standard data model can then be used to create segments. These groups of individuals can then be shared with Marketing Cloud to initiate multi-step marketing campaigns.

Being able to predict expected revenue, the likelihood of case escalation, delivery times, and purchase propensity, while tying the data to a unified individual, helps marketers send the most relevant communications to customers while maximizing campaign spend.

Data + AI is how you power consistent, accurate, and personalized marketing campaigns using data across your enterprise.


Salesforce has a suite of products that bring Data + AI into the hands of customers, employees, and partners. Getting insights and taking action on data changes in your enterprise drives tangible business benefits — like shortening the time it takes to close a case, predicting the next product a customer is likely to be interested in, or getting help crafting an introductory email to a prospect.

Data Cloud and Salesforce’s artificial intelligence form an important foundation that developers can now utilize to drive new capabilities using data and AI models that were previously unattainable.

Check out the resources section to get hands-on with Data Cloud. We can’t wait to see what you create.

The high-level interactions between applications and services in Salesforce Customer 360.


About the author

Dave Norris is a Developer Advocate at Salesforce. He’s passionate about making technical subjects broadly accessible to a diverse audience. Dave has been with Salesforce for over a decade, has over 35 Salesforce and MuleSoft certifications, and became a Salesforce Certified Technical Architect in 2013.

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