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Power Automation with Flows and Agents

Learning Objectives

After completing this unit, you’ll be able to:

  • List some use cases for using Data 360 in flows.
  • Describe the benefits of building agents on a Data 360 foundation.

Data 360 in Flows

Flows are an automation tool that can access your Data 360 data. You can create interactive or triggered automations that use or react to both external data (like website activity or mobile app usage) and internal Salesforce data (like CRM records), all harmonized within Data 360.

In flows, you can access data stored in data model objects (DMOs) and the results of calculated insight objects (CIOs), but not raw data lake objects (DLOs). Here are some use cases for automating processes with Data 360.

  • Keep data consistent across systems: You can use flows to retrieve DMO data, such as contact point information, and keep your Salesforce records in sync with external databases. For example, automatically populate a contact’s External ID and phone number in Salesforce based on contact info found in an external data source.
  • Trigger actions from DMO changes: Flows can be triggered directly by changes in DMO data. For example, automatically send an email to a guest when their loyalty level, stored in an external guest loyalty object (DMO), is updated to “Diamond”.
  • Trigger actions from calculated insights changes: Flows can also respond to changes in the results of your calculated insight objects (CIOs). For instance, if a “Number of Abandoned Carts” CIO reaches a threshold of three or more, a flow can automatically create a case for the sales team to follow up.

Data 360-Powered Agents

Data 360 is essential for effective, personalized, and trusted agents within Agentforce. It provides the data foundation that agents need to truly understand and interact with your customers and business. Here's how Data 360 powers your AI agents.

  • Unified customer 360 data: Agents built on Data 360 have access to unified customer 360 profiles, meaning they know your customers deeply across all interactions—from purchases in Sales Cloud to engagements in Marketing Cloud. This enables them to provide highly personalized responses, like recommending a specific product to a customer based on their recent purchases and engagement with marketing campaigns.
  • Clean and transformed data: Cleanse and prepare data with batch and streaming data transforms, resolving inconsistencies. This improves agent accuracy, consistency, and reliability, preventing incorrect or ambiguous responses.
  • Real-time capabilities: Agents can react to current customer actions in seconds, using real-time data ingestion and analysis. For example, agents can tailor their responses based on what the customer is currently browsing online.
  • Zero-copy data: Data 360 allows agents to expand their knowledge beyond Salesforce by connecting to external data sources using zero-copy data federation.
  • Retrieval augmented generation (RAG): Data 360 is crucial for grounding prompts to large language models (LLMs) through RAG. It provides the contextual and specific information needed to enhance the quality, accuracy, and relevance of AI-generated outputs.
  • AI guardrails and analytics: Data 360 powers critical AI governance features. The Einstein Trust Layer protects customer data with security features like zero data retention, toxicity detection, and secure data retrieval. The Generative AI Audit and Feedback trail logs prompt IDs, user data, text, and safety scores, allowing you to monitor agent actions and outputs. Agentforce Analytics stores and processes data in Data 360, displaying prebuilt and custom dashboards to track agent performance, user trends, and acceptance rates.

Next Steps

In this module, you explored how Data 360 connects and unifies your enterprise data, turning it into actionable insights for sales, service, and advertising, and how it powers intelligent automation through flows and agents. Next, in the Advertising with Data Cloud module, learn how first-party data in Data 360 personalizes your marketing campaigns.

At the end of the trail, wrap up your learning in the Cert Prep: Data Cloud Consultant module. While getting the certification isn’t a requirement, this trail covers the learning objectives tested in the certification exam. Complete the module to test your knowledge and consider completing the full exam.

Resources

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