The absence of data refers to scenarios where you would like to take action on data that is not typically stored in a table/database.

In order to help you identify an absence of data, Gainsight offers a feature in the Rules Engine that allows you to take the appropriate action for records that do not have data for the object fields selected in the Show section. This feature can be enabled when setting up a rule using the Include accounts where data is unavailable toggle button.

Following are some examples where Absence of Data is required:

  • Set NA Score when a customer hasn’t put Case data in last x days.

  • Create a CTA if no Timeline activity for an action last x days.

  • No email opens in the last x days.

  • Accounts with no CTAs.

  • Accounts with no Usage.

Step 1: Query Accounts that have Data 

In an ideal dataset, one row of data per account must be present. 

In this example, the dataset will bring back how many total clicks were performed by an account in the last 90 days.

Step1.png

  1. Create a Bionic Rule. 
  2. In the Setup Rule screen, select Matrix Data as the source and create a fetch task using the MDA Usage Data object. 
  3. Add Account and SUM of Clicks as the Show fields. 
  4. In the Filters section, add Date field. 
  5. Select the operator greater than and select Subtract 90 Days from Rule Date. 
  6. Provide a name for the task and click Save. 

Step 2: Fetch Valid Gainsight Customers

In this step, valid Gainsight customers are filtered using the CustomerInfo object. 

  1. Create another fetch task. 
  2. Select Salesforce as the source.
  3. Select CustomerInfo as the object. 
  4. Add Account as the Show field.
  5. In the Filters section, add the Status = Active filter. 
  6. Select Apply to Gainsight Customers Only check box. 

Step2.png

Step 3: Merge Valid Gainsight Customers

Use a Bionic Merge Task to join your data fetch (step 1) to the valid Gainsight Customer List (Step 2). It's important for the Gainsight Customer Fetch (Step 2) to be included as well as a Left Join. In the field highlighted below, Output field name from Data Fetch side was changed to “Account ID From Usage”. This is the field that will be recognized in the action to filter for accounts without data.

Note: You may want to do a right join if you want to identify usage data without valid Customer Info. Rules will display an error “Invalid Cross reference id or Entity Deleted” in response to such usage records.

  1. In the Merge task, select the output of Step 1 with Step 2 and select Retain all records on left. 
  2. In the Show Fields section, change the Output Field Label of the Account as Account ID from Usage. 
  3. Click SAVE. 

Step 3.png

Step 4: Previewing Data from Merge Task

After saving the Merge Task you can head to the Action Page and click Run Now as a test run. This is allowed without having to make an action. You can then download the results of the last task to view in rules read only mode > Execution History.

Step4.png

Resulting Data Set from Merge

The resulting data set from the merge task: 

Account

Clicks

Account_ID

00137000004IzdFAAS

1115440

00137000004IzdFAAS

001370000065CYJAA2

1952020

001370000065CYJAA2

0013700000K5xlwAAB

 

 

001370000031X7PAAU

 

 

001370000031X7QAAU

 

 

00137000004IzQVAA0

 

 

Step 5: Adding Actions to Data

To add actions on the data above, a simple filter criteria can be used to filter accounts without activities or absent data.

Note: If you have more than one action, make sure to have other actions set to “Account ID From Usage” != null. This will prevent the action from evaluating nulls when intended to evaluate on positive data. 

Step5.png