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Create a Story

Note

Note

Einstein Analytics has a new name. Say “Hello,” to Tableau CRM. Everything about how it works stays the same. Tableau CRM offers the best experience for native analytics inside Salesforce CRM products. It continues to combine artificial intelligence (AI) and business intelligence (BI), and Einstein Discovery continues to have tight integration with the platform. You’ll see the old name in a few places as we work through the updates.

Learning Objectives

After completing this unit, you’ll be able to:
  • Create an Einstein Analytics dataset and import data into it.
  • Use your imported data to create a story.

Introduction

If you completed the Einstein Discovery Stories module, you already know about Einstein Discovery stories. You use Einstein Discovery stories to analyze data in Einstein Analytics datasets and produce insights into that data. Einstein Discovery performs a comprehensive statistical analysis of the data using AI and machine learning. A story helps you uncover relationships between a business-relevant outcome, and the explanatory variables that are potential influencers of that outcome. An outcome, typically a key performance indicator (KPI) for your business, is sometimes referred to as the outcome variable in a story.

In this module, you learn how work with two other types of insights:
  • Why It Happened insights are diagnostic insights that give you a deeper understanding of the complex relationships in your existing data. These insights identify factors and combinations of factors that have a significant impact on the outcome.
  • What Could Happen insights provide predictive insights that predict future outcomes, and prescriptive insights that recommend ways in which to improve the predicted outcome. Predictions aren’t a guarantee of future results. But Einstein Discovery can give you a better idea of how things might turn out based on what it’s learned from the data you provided. Einstein also suggests ways in which you can improve the predicted outcome.

To get started, let's upload some data and create a story to work with.

Note

Note

We recommend that you complete the Einstein Discovery Stories module before starting this module. If you did the Einstein Discovery Stories module recently, skip the next few steps. Instead, launch your Analytics-enabled DE org and open the AcquiredAccount-based story you created in that module.

Try Einstein Discovery with a Developer Edition Org

Before you work through this Trailhead module, sign up for a free Analytics-enabled Developer Edition org. This org is a safe environment where you can practice the skills you’re learning.

Important

Important

For this trail, you can’t use an existing Developer Edition org. Instead, sign up for this special Analytics-enabled Developer Edition org because:

  • It comes provisioned with the Analytics Plus license required for Einstein Discovery.
  • It has Einstein Discovery enabled.
  • It has the Einstein Analytics Plus permission set needed to use Einstein Discovery features.

Even if you already have an Analytics-enabled Developer Edition org, sign up for a new one now. The older Analytics-enabled Developer Edition orgs don’t get recently released features. Signing up for a new one ensures that you get the latest and greatest features.

Signed up? Great! Let's jump right in!

Download the Data

Before we can create the story we use in this module, we need the data to analyze. Download the CSV file called AcquiredAccount.csv and save it to your computer.

The CSV file contains the same data that is used in the Einstein Discovery Stories module. We provide it as a shortcut so you can work through this module without having to finish the previous module first.

The CSV file has 11 columns. It contains one row of information for each of the 10,000 different companies that our auto parts manufacturing company does business with. Here is what the first few rows of the CSV file look like.

First rows of the CSV file

Create and Populate an Einstein Analytics Dataset

The next step is to get the data from the CSV file into an Einstein Analytics dataset.

  1. In your new DE Org, switch to Lightning Experience (if you have not already done so).
  2. From the App Launcher (App Launcher icon), find and select Analytics Studio.
  3. Click Datasets.
  4. Click Create and then select Dataset from the dropdown.
  5. Choose CSV File as the source for your new data.
  6. In the file-selection window that opens, find and select (or drag and drop) the AcquiredAccount.csv file you downloaded, and then click Next.
  7. Accept the defaults and click Next.
  8. Accept the defaults and click Upload File. Einstein Analytics creates a dataset and imports the data from the CSV file.

Create the Story

Now, you’re ready to create a story from this dataset. Begin by telling Einstein Discovery which outcome variable to focus on. In this module, we want our story to maximize on the CLV variable. If you did the Einstein Discovery Stories module, you are familiar with this variable. Customer lifetime value (CLV) is a metric that predicts the profitability over the entire lifetime of the company’s relationship with a customer. Looking at CLV can help you find the best customers.

To create a story:

  1. Hover over the dataset, click the dropdown, and click Create Story. Analytics Studio launches the Story Setup wizard.
  2. In the first screen, for The field, select CLV as the outcome that you want Einstein to analyze.
  3. Accept all other defaults and click Story Type.
  4. In the Story Type screen, click Insights & Predictions, then click Setup Options.
  5. In the Setup Options screen, select Manual and click Data OptionsData optionsNotice that the selected outcome variable is first in the list. The remaining columns represent explanatory variables. An explanatory variable is a variable that you explore to determine whether, and to what degree, it can influence the outcome variable for your story.

    In the Correlation column, Einstein shows you the percentage by which each field is statistically correlated to the outcome. The Division field has the highest correlation. However, Account Id has the second highest correlation. That’s curious. Why? Let’s stop and think for a moment. Does an arbitrarily assigned account ID have any influence on CLV? Probably not. We know that because we know our business. In this case, statistical significance does not translate to real-world significance. Therefore, let's remove this field from our analysis to speed up the analysis and get clearer results.
  6. Clear the check box next to Account Id.
  7. Click Create Story

When it’s done analyzing your data and discovering insights, Einstein Discovery shows you the results.

CLV by Division insight

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