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.