Unlock Success with Einstein Next Best Action in Salesforce

Unlock Success with Einstein Next Best Action in Salesforce

Table of Contents

• Introduction
• What is Einstein Next Best Action?
• Benefits of Einstein Next Best Action
• Use Cases of Einstein Next Best Action
• Planning for Einstein Next Best Action
• Five Phases of Setting Up Einstein Next Best Action
  • Phase 1: Creating an Action Flow
  • Phase 2: Creating a Recommendation
  • Phase 3: Building a Recommendation Strategy Flow
  • Phase 4: Displaying Recommendations to Users
  • Phase 5: Analysis and Iteration
• Demo: Using Einstein Next Best Action
• Resources for Success
• Conclusion

Introduction

Salesforce Einstein Next Best Action is an advanced process automation tool that leverages artificial intelligence (AI) to provide personalized recommendations for employees and customers in real-time. By automatically suggesting the next best action, Einstein Next Best Action helps businesses streamline decision-making, enhance customer experiences, and drive increased productivity. In this article, we will explore the functionality, benefits, use cases, and implementation process of Einstein Next Best Action.

What is Einstein Next Best Action?

Einstein Next Best Action is an AI-powered tool that presents personalized recommendations to users based on their interactions, context, and historical data. It automates the follow-up actions and decisions, saving time on manual processes. With integration with AI and ML tools like Einstein Recommendation Builder, the recommendations provided by Next Best Action get smarter over time.

Benefits of Einstein Next Best Action

Einstein Next Best Action offers numerous benefits for businesses, employees, and customers. Some of the key advantages include:

• Empowering employees to make better decisions and take actions faster
• Personalizing real-time offers to customers
• Driving increased productivity, customer satisfaction, and revenue
• Enhancing the overall customer experience by providing tailored and connected interactions

Use Cases of Einstein Next Best Action

Einstein Next Best Action can be applied across various departments and industries. Some common use cases include:

• Providing sales teams with contextual insights about leads and opportunities
• Alerting service agents of potential upsell and cross-sell opportunities
• Recommending offers to customers based on their interactions with marketing campaigns

Planning for Einstein Next Best Action

Before implementing Einstein Next Best Action, proper planning is essential. Consider the following points:

• Identify the processes or problems that can be improved with recommendations
• Define the target audience and the decisions you want them to make
• Determine the conditions for recommendations to surface
• Decide on the actions to occur when a recommendation is accepted or rejected
• Plan where and how to display the recommendations
• Set adoption goals and success metrics for the implementation

Five Phases of Setting Up Einstein Next Best Action

To successfully set up and deploy Einstein Next Best Action, the following five phases need to be followed:

Phase 1: Creating an Action Flow

• Create an action flow using Flow Builder, which will be triggered when a user accepts or rejects a recommendation.
• Choose between a screen flow or an auto launch flow based on the need for user interaction.
• Define the flow actions to be performed automatically in the background.

Phase 2: Creating a Recommendation

• Create recommendations manually using the Recommendations object.
• Design the recommendation description and select the associated action flow.
• Categorize the recommendation based on Relevant fields for better filtering and reporting.

Phase 3: Building a Recommendation Strategy Flow

• Use Flow Builder to create a recommendation strategy flow.
• Retrieve and store recommendation records based on criteria defined in the flow.
• Use assignment elements to pass the recommendations into the output recommendations variable.

Phase 4: Displaying Recommendations to Users

• Navigate to the Lightning App Builder to add the Einstein Next Best Action component to the relevant page layout.
• Configure the component properties, including the recommendation strategy source and display options.
• Save the page layout changes to display the filtered recommendations to end users.

Phase 5: Analysis and Iteration

• Conduct A/B testing and analyze the performance of recommendations.
• Create reports to track recommendation data and user responses.
• Refine recommendations based on adoption goals and success metrics to improve strategies.

Demo: Using Einstein Next Best Action

Let's consider a use case where customers call a service center to report hardware issues that may require a field technician. By leveraging Einstein Next Best Action, we can proactively recommend dispatching a technician when the case matches certain criteria. After accepting the recommendation, the user can confirm the dispatch, update the case status, and send a confirmation email to the customer. The goals of this demo are to increase customer satisfaction and decrease time to resolution.

Resources for Success

To learn more about using Einstein Next Best Action and ensure a successful implementation, the following resources are available:

• Complete the interactive trailhead on Einstein Next Best Action.
• Join the Einstein Next Best Action Trailblazer Community to discuss best practices and connect with other users.
• Explore the "Automating with Salesforce Flow" expert Coaching session for additional insights and how-to's.
• Stay updated with the latest product details by joining the Release Readiness discussion group and reviewing release notes.

Conclusion

Salesforce Einstein Next Best Action is a powerful tool that enables businesses to provide personalized recommendations based on AI insights. By automating decision-making and actions, businesses can enhance productivity, customer satisfaction, and overall revenue. With proper planning and implementation, Einstein Next Best Action can be a Game-changer for organizations looking to streamline processes and improve customer experiences.