Learn Einstein Discovery

Einstein Discovery and its stories are a powerful part of CRM Analytics allowing users to create point-and-click predictions. On this page, you will find a collection of blogs to help you understand what Einstein Discovery can do and how you can create predictions in your organization. If you want more make sure to check out this collection on assets.

Define your use case
Gather & prepare data
Discover, analyze & strategize on your insights
Create predictive models
Deploy models & create AI-enhanced workflows
Einstein Discovery in Tableau
Manage your implementations

Define your use case

“Every great ML project starts with a great use case. ” Establish and clearly define the business goal. What business process do you want to improve? Who are the users and what will they do? Define what KPI will measure the goal. Envision what the AI-augmented workflows will look like.

Staying focused – Using a methodology to organize your thoughts and project activities

Understand how the steps in an Einstein Discovery project and how to create a good use case.

March 9, 2020 / Colin / Add Intelligence, Deployment and Packaging, Winter 20

Estimate Propensity to Buy with Einstein Discovery to improve sales excellence

A use-case where we are using Einstein Discovery to find the best product fit to a customer.

June 8, 2020 / Olfa Kharrat / Add Intelligence, Spring 20, Use Case

Accelerating Prescriptive Analytics Using Einstein Discovery Templates

A practical use case leveraging story templates to get any Salesforce admin started with Einstein Discovery and predictive analytics.

December 17, 2020 / Itamar Zik / Add Intelligence, Stories, Winter 21

Intelligent Pipeline Management with Einstein Discovery

A walk-through of how to use Einstein Discovery for opportunity scoring and make your sales pipeline more intelligent.

June 8, 2021 / Reinier van Leuken / Add Intelligence, Stories, Summer 21

Predicting the best up-sell with Einstein Discovery Multiclass models

Explore some use cases for multiclass models and what it means.

January 31, 2022 / Reinier van Leuken / Add Intelligence, Spring 22, Stories

Gather and Prepare data

Find data sources. Establish a means of labeling, cleaning, joining, and aggregating the data through Salesforce or other tools.

Preparing Your Data For Einstein Discovery

A practical example of how to model your data for an Einstein Discovery story of “Minimize Time to Close”.

March 11, 2020 / Bobby Brill / Add Intelligence, Data Prep, Spring 20

Discover, Analyze & Strategize on your Insights

Discover correlations and drivers in your data. Analyze it for insights. Create segmentations. Understand the conditions that create the greatest value. Strategize how these findings can be implemented into new experiences for your org.

What are Einstein Analytics Stories and when would you use them?

Understand how to formulate your business questions for predictive purposes.

February 5, 2020 / Rikke Hovgaard / Add Intelligence, Stories, Winter 20

What kind of questions can Einstein Analytics Stories answer?

Understand what Einstein Discovery stories are including the benefits and possibilities.

February 17, 2020 / Rikke Hovgaard / Add Intelligence, Spring 20, Stories

Create Predictive Models

Create an instantiation of a model – to generate predictions for future events. Tune it until you are satisfied with its performance. Ensure you’re meeting your evaluation criteria. Dark launch the model in your org. Measure the difference between the predicted and actual values. Find and remove data leakage.

Einstein Discovery: How good is my model really?

Understand how to evaluate if your predictive model is good.

September 17, 2019 / Olfa Kharrat / Add Intelligence, Model Theory, Summer 19

Take your Einstein Discovery model from Good to Great

Understand how what options you have to improve your model.

October 30, 2019 / Olfa Kharrat / Add Intelligence, Stories, Winter 20

The Delicacy of Accuracy: A Deep Dive on Classification Performance

Taking a closer look at binary (true/false) model metrics.

May 26, 2020 / Reinier van Leuken / Add Intelligence, Model Theory, Spring 20

Tree-Based Learning Algorithms in Einstein Discovery

Understand how the tree-based models work in Einstein Discovery and how you can apply them to your stories.

June 22, 2020 / Darvish Shadravan / Add Intelligence, Model Theory, Summer 20

Einstein Discovery: How much data for a good story?

Learn how much data do you need in your dataset to create a good story.

January 19, 2022 / Reinier van Leuken / Add Intelligence, Spring 22, Stories

Einstein Discovery: What is Cardinality, and why should I care?

Data cardinality is an important concept when it comes to Einstein Discovery, but what does it mean exactly? And what considerations should you have around cardinality? Check out this short video to get the answers.

February 24, 2022 / Reinier van Leuken / Add Intelligence, Spring 22, Stories

Deploy Models & Create AI-enhanced Workflows

Partner with your users to develop the interfaces and workflows that enhance their productivity – for both IC’s and management. Prototype the designs and implementation.

Create Intelligent Applications with the ‘Predict’ node in Recipes

Einstein Discovery in Tableau

Deploy models specifically for integration in Tableau. Native integration to the world’s leading analytics platform, consume model outcomes in different ways.

Einstein Discovery in Tableau – Try it for Yourself

A step-by-step walkthrough of how to deploy your stories to Tableau.

March 25, 2021 / Bobby Brill / Add Intelligence, Custom Extensions, Spring 21

Manage your Implementations

Following up on your models after they have been deployed.

Managing Einstein Discovery Models in the Wild

Detecting drift and maintaining your model performance after deployment.

May 11, 2020 / Reinier van Leuken / Add Intelligence, Spring 20, Stories

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