Create a Story
- Create a Tableau CRM dataset and import data into it.
- Use your imported data to create an Einstein Discovery story.
If you completed the Einstein Discovery Stories module, you already know about Einstein Discovery stories. You use Einstein Discovery stories to analyze data in Tableau CRM datasets and produce insights into that data. Einstein Discovery performs a comprehensive statistical analysis of the data using machine learning and AI. A story helps you uncover relationships between a business-relevant outcome and the explanatory variables that are potential influencers of that outcome. The 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 the following types of insights:
- Diagnostic insights 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.
- Predictions provide predictive insights that predict future outcomes. Improvements provide and prescriptive insights that recommend ways in which to improve the predicted outcome, respectively. Predictions and improvements 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.
To get started, let's upload some data and create a story to work with.
Try Einstein Discovery with a Developer Edition Org
For this trail, you can’t use an existing Developer Edition org. Instead, sign up for this special Tableau CRM-enabled Developer Edition org because:
- It comes provisioned with the Tableau. CRM Plus license required for Einstein Discovery.
- It has the Tableau CRM Plus permission set needed to use Einstein Discovery features.
Even if you already have an Tableau CRM-enabled Developer Edition org, sign up for a new one now. The older Tableau CRM-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!
Before you work through this Trailhead module, sign up for a free Tableau CRM-enabled Developer Edition org. This org is a safe environment where you can practice the skills you’re learning.
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 here for convenience so that 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.
Create and Populate a Tableau CRM Dataset
The next step is to get the data from the CSV file into a Tableau CRM dataset.
- From the App Launcher (), find and select Analytics Studio.
- Click Datasets.
- Click Create and then select Dataset from the dropdown.
- Choose CSV File as the source for your new data.
- In the file-selection window that opens, find and select (or drag and drop) the AcquiredAccount.csv file you downloaded, and then click Next.
- Accept the defaults and click Next.
- Accept the defaults and click Upload File. Tableau CRM 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 Customer Lifetime Value (CLV). If you did the Einstein Discovery Stories module, you are already familiar with this metric, which 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:
- Hover over the dataset, click the dropdown, and click Create Story. Analytics Studio launches the Story Setup wizard.
- In the first screen, for The field, select CLV as the outcome that you want Einstein to analyze.
- Accept all other defaults and click Story Type.
- In the Story Type screen, click Insights & Predictions, then click Setup Options.
- In the Setup Options screen, select Manual and click Data Options. Notice that the selected outcome variable (CLV) 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.
- Clear the check box next to Account Id.
- Click Create Story
When it’s done analyzing your data and discovering insights, Einstein Discovery shows you the results.
Here are the key areas of the interface for Einstein Discovery stories:
Name of this story, selected goal, most recent version.
Tools you can use to view predictions and improvements, update story settings, and other tasks.
Shows you the list of variables in your story and their correlation to the story outcome.
|4||Story Version Summary||
Summary of story insights, including version comparison.
|5||Insights List||List of insights associated with this story.|