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Use the Einstein Platform

Learning Objectives

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

  • Explain how the Einstein Platform allows any admin or developer to build their own smart assistant.
  • List each Einstein Platform product.

Build Your Own Smart Assistant

Like you learned in the last unit, Einstein out-of-the-box features are available across every Salesforce cloud. But we all know that Salesforce admins and developers customize their Salesforce instance for the unique ways that their business interacts with its customers. Fortunately, there are tons of ways to customize Salesforce, but what about customizing Salesforce Einstein?

The Einstein Platform allows all admins and developers to build their own AI-powered assistants for a wide array of use cases. You can use point-and-click and programmatic functionality to build applications that predict anything surfaced through Salesforce. 

All of the Einstein Platform products incorporate one or several of the smart assistant components we told you about in the first unit. Read on to dive into the platform products that enable you to build your own smart assistant.

Einstein Bots

Einstein Bots allow you to build a smart assistant into your customers’ favorite channels like chat, messaging or voice. Einstein Bots use Natural Language Processing (NLP) to provide instant help for customers by answering common questions or gathering the right information to handoff the conversation seamlessly to the right agent for more complex questions or cases. 

Say you’re an ecommerce business, and your service team gets loads of inquiries, through many different channels. With Einstein Bots you can create chatbots for your business to immediately answer specific, routine questions for customers like updating passwords or order status updates. This results in more time for service agents to work on the complex, nuanced cases, and customers save time by getting their answer fast. And if an Einstein Bot doesn’t have the answer at the moment, your customers can be instantly welcomed with a branded greeting in a chat window, directing them to the right agent to help them, fast. Considering customers live in an instant, mobile, web-driven world, they expect one-to-one service—immediately. If they don’t get a swift response, they can think less of a brand. Einstein Bots eliminates that friction.

Corresponding visual on how Einstein Bots works

Einstein Prediction Builder

Einstein Prediction Builder is a simple point-click wizard that allows you to make custom predictions on your non-encrypted Salesforce data, fast. You can create predictions for any part of your business—across sales, service, marketing, commerce, IT, finance, and even HR—with clicks, not code. 

When it comes to understanding how to apply Prediction Builder to your business, ask yourself which objects and fields you want to predict.

  • Do I want to predict the answer to a yes or no question? (Binary Classification)
    • Is this zip code a good opportunity for my business?
    • Will this customer attrit?
    • Does a new employee require a particular type of training?
    • Will a flight arrive on time?
    • Will a customer miss a payment?
  • Do I want to predict an amount? (Regression—in Beta)
    • For what price can we sell this home for?

Say you’re a consumer goods company that sells to retail stores, and you’ve been having a large problem recently with some stores terminating their purchases of your products. Because of that, you want to provide a prediction for your service reps on whether a retail store will attrit. With Prediction Builder, you can choose the object you want to predict on, in this case “retail store” and the field you want to make a prediction for, in this case “attrition?”. Then, you bring in the dataset that includes all of the line items for “retail store” and whether or not they’ve attrited, along with other characteristics surrounding the customers, and AutoML will do its magic in the backend. 

Finally, Prediction Builder will provide you with a percent likelihood of whether a customer will attrit (for all of the customers who have a blank field for “attrition?”), and the top positive and negative features surrounding the prediction.

Example of a prediction surfaced through Salesforce console

Now that your service reps have this valuable information, they know which customers to engage with, and they have a better idea on how to engage with them to prevent attrition. Ultimately, this will lead to fewer lost opportunities and more revenue for your business.

Einstein Next Best Action

Einstein Next Best Action (NBA) allows you to use rules-based and predictive models to provide anyone in your business with intelligent, contextual recommendations and offers. Actions are delivered at the moment of maximum impact—surfacing insights directly within Salesforce.

Let’s bring back the same scenario where your business was struggling with customer attrition, and you had already built a predictive model for your service reps to see which customers were likely to attrit versus others. Now, what if you could give your service reps the right recommendations to offer the customer to keep them from attriting?

With Next Best Action, you create rules, or propositions, based off of predictions and outcomes, to surface the best recommendation for your service reps to recommend to customers. Say you create a proposition on recommending a 10% discount on two-year contract extensions to customers who have an 80% or higher likelihood of attrition. As your service reps come across predictions of customers who fall in that category, they’ll be recommended right in the Lightning Console to follow up with them and send the 10% discount, and they can take that action instantly, all from Salesforce.

Creating a proposition inside Salesforce console

Example of creating a strategy that takes filters out low likelihoods of attrition

The thing is, there are so many different combinations of follow-up tactics to create for different scenarios for all businesses, so having propositions automatically surfaced in Salesforce, straight to your users helps take the guesswork out of their day.

Example of recommendations in Salesforce console

Einstein Discovery

Like Einstein Prediction Builder, Einstein Discovery also predicts outcomes without requiring your own data scientist.

Let’s go back to the problem of customer attrition in the Prediction Builder example. Let’s say your consumer goods business has some analysts who work with different teams to optimize operations. And your business has troves of data housed in Salesforce with strict data requirements. There are important fields in your Salesforce instance that can help predict customer attrition. Your service reps, who are receiving predictions through the Lightning Service Console from Prediction Builder, start to realize that a few customers are at risk of attrition. Prediction Builder tells them some high-level reasons why, but the service reps want to get to the bottom of the problem. 

With Einstein Discovery, anyone can get the full understanding of relevant patterns on all of the data in your company, whether encrypted or not, to make predictions on customer attrition. You can have full control of the data they’re putting into the predictive model and be able to dig deeper into the predictions and insights. 

For example, Einstein Prediction Builder will show the service reps that a customer is likely to attrit because their last purchase was 3 months ago. Also, their store isn’t located in a region where your products are in high demand. With that insight, how does a service rep respond? Which insight is more important than the other? Einstein Discovery can answer that for you. What if it tells you that consumer demand in a certain retail location is more important? With that insight, your service teams can work with sales, marketing, and product teams to design products that meet the demand for that location, or boost marketing in those areas to increase awareness of the products.

example of predicting what will happen and corresponding graph with Einstein Discovery

Einstein and Generative AI

The latest Salesforce Einstein innovation is generative AI with Einstein. The rise of generative AI has sparked one of the most significant technological shifts in business since the introduction of the internet. Generative AI, such as ChatGPT, is set to transform how organizations and their customers interact, leading to more personalized, collaborative, and conversational connections.

Einstein allows businesses to generate personalized and relevant content by grounding large language models (LLMs) in their CRM data safely and securely. 

It’s built on Hyperforce, our trusted infrastructure platform, to address data privacy and compliance concerns with our best-in-class security guardrails. Einstein GPT is also highly customer aware with pre-built connections to Data Cloud, offering real-time insights on the billions of customer events that occur daily. That means that every piece of content generated, whether it’s an email, a report, a knowledge article or a piece of code, is hyper-relevant to your customers.

To get started with Einstein and generative AI, you can choose from an open and extensible ecosystem of models, which includes proprietary Salesforce models or public models from partners like OpenAI or Anthropic, or bring your own model. To ensure that sensitive data isn’t retained by public models, the Salesforce zero-retention architecture mandates that customer data is never stored outside of Salesforce. This gives you peace of mind that your customer data is being used safely and responsibly within the trust boundary of Salesforce. 

Using generative AI with Einstein creates more tailored experiences Einstein 1 by using conversational intelligence to help you close deals faster, resolve service inquiries in record time, improve customer relationships, and ultimately increase revenue. For example, if you are a sales rep looking to craft an email for one of your accounts, Einstein can help you pull in relevant context such as the main point of contact for the account, example emails, the latest news, and the last interaction with that customer. Using CRM data, Einstein can also automatically embed relevant offers and promotions to help you close that deal. The result is an email safely grounded in customer data and personalized with tailored offers. Once the email is generated, none of that private customer data is retained by the model, and the sales rep always has the ability to review the email before it’s sent.

Ready to Get Your Einstein On?

Now you’ve seen some of what Einstein has to offer. Continue to explore topics of interest to you by checking out the Resources section below.


Rights of ALBERT EINSTEIN are used with permission of The Hebrew University of Jerusalem. Represented exclusively by Greenlight.

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