Salesforce Personalization

Salesforce Personalization in Marketing Cloud Next is a Customer 360 application that uses Data 360 to provide personalized experiences across Salesforce clouds.

• About Salesforce Personalization
  Salesforce Personalization Marketing Cloud Next works with Data 360 to provide personalized experiences across Salesforce clouds. It uses objective-based (using ML), or rules-based content recommenders to deliver personalized experiences to customers across channels. For simple use cases, you can also configure rules to surface specific content assets.
• Setup Guide: Data 360 for Salesforce Personalization
  This guide covers the steps to set up Data 360 to support Salesforce Personalization for Marketing Cloud Next. It outlines basic recommendations, so that your team can get up and running. For in-depth information, special features, or customization options, we provide additional resources along the way.
• Salesforce Personalization and Data 360 Setup
  Salesforce Personalization in Marketing Cloud Next is a Customer 360 application that connects and provides personalized experiences across clouds. To use Salesforce Personalization, define the appropriate permissions, and install and configure Data 360 to work with Personalization data model objects.
• Engagement Signals and Metrics
  Create engagement signals and metrics to track interactions across channels as individuals engage with your brand. You can then use these engagement signals when creating objective-based recommenders to deliver personalized recommendations with Salesforce Personalization in Marketing Cloud Next.
• Calculated Affinities
  Calculated affinities enable you to gauge an individual’s interest in objects and their selected attributes. The output of a calculated affinity provides a numerical score to indicate preference. Personalization uses this value in segmentation, decision targeting, recommendation filtering, and when grounding Salesforce AI Agents to improve decision-making, enhance personalized output, and build trust.
• Creating and Training Salesforce Personalization Recommenders
  Salesforce Personalization in Marketing Cloud Next generates multichannel, focused, and individualized recommendations based off of deep, digital, and offline behavioral and business context data. To create personalized recommendations, you configure a recommender and train it using Data 360 data graphs that you select.
• Personalization Points in Salesforce Personalization
  Use Salesforce Personalization in Marketing Cloud Next to create a personalization point. This object delivers personalized content by tying together a data space, profile data graph, personalization type, and response template. After you define these entities, you can add decisions and targeting rules to the personalization point.
• Experimentation
  Experiments provide customer insights that help you make better decisions. Create experiments with Salesforce Personalization in Marketing Cloud Next to learn which personalized and agentic experiences resonate best with your customers.
• Salesforce Personalization Analytics
  Analytics for Salesforce Personalization in Marketing Cloud Next are designed to provide insights into how your app is running, and the effectiveness of your personalization program. To gain operational insights, you can use the Personalization pipeline intelligence dashboard. To understand personalization effectiveness and performance, you can use the attribution dashboard. The attribution dashboard enables you to visualize preconfigured, ready-to-use attribution configurations available through personalization setup, or custom attribution configurations that you define. You can also visualize any personalization analytics DMOs using Tableau or any JDBC-compatible client.
• Agentforce for Salesforce Personalization
  Learn how Agentforce for Salesforce Personalization in Marketing Cloud Next creates and delivers personalized recommendations, content, and how it can provide essential contextual data for other agents.
• Web Personalization Manager for Salesforce Personalization
  Salesforce Personalization in Marketing Cloud Next can manage personalized content on non-Salesforce websites. Use Web Personalization Manager to create and refresh tailored experiences that appear at the right moment and location using customer interaction data captured by Salesforce Interactions Web SDK, along with AI-driven recommendations. You can create multiple personalization experiences and designate specific ones for different pages of your website, improving relevance and visitor engagement.
• Batch Personalization Decisions for Customer Segments
  With Batch Personalizations, you can create personalized decisions for a Data 360 segment and save the decisions to Data Model Objects (DMO) in Data 360. You can then send the batch personalization output to other platforms like Marketing Cloud Engagement (MCE), Google Cloud Platform (GCP), Amazon S3, and Azure to power your cross-channel marketing campaigns. For example, using Data 360, Salesforce Personalization, and MCE, you can use recommendations created for a Data 360 customer segment in MCE emails to notify your customers about an upcoming year-end sale.
• Einstein Studio Model Predictions for Personalization
  Use real-time predictions from Einstein Studio models in Salesforce Personalization targeting rules to refine your personalization decisions. For example, consider you have a predictive model in Einstein Studio that predicts the chances of customers buying an item from your website. You can use this output in your targeting rules to determine the customers eligible for a special discount.
• Salesforce Personalization References
  Use these references when configuring or validating Salesforce Data 360 calculated insights for using Salesforce Personalization in Marketing Cloud Next.