Gainsight NXTThis article supports Gainsight NXT which is built on Gainsight's state of the art Matrix Data Architecture (MDA) platform, and is designed for customer success professionals for driving revenue, increasing retention, and scaling operations. To learn more about Gainsight NXT, click here.
If you are using Gainsight Salesforce Edition, which is built on Salesforce and customer business data is stored in SFDC, you can find supporting documentation here.
Create Tasks with Rules Engine
This article provides guidelines on how Admins fetch data from Matrix Data Architecture (MDA) and perform actions using Gainsight’s Rules Engine that has the capability to transform fetched data in various ways and execute actions with a single Rule. Users can perform Historical Rule Executions faster using Rules Engine because of the data volume.
Before you start exploring how to create tasks using Rules Engine, ensure that you have read the Getting Started with Gainsight Rules article.
Fetch Data from MDA
- Navigate to Rules Engine > RULES LIST tab.
- Click +RULE. The Create Rule screen is displayed.
- Provide the following in the Create Rule screen:
- Select the Rule for a Company.
- Enter a Rule Name.
- Enter Description [Optional].
- Click NEXT. You are navigated to the Setup Rule screen.
- Click DATASET TASK.
- Enter the Task Name, Task Description, and Output Dataset Name. If you do not provide a value in the Task Name field, it is auto populated as per the format Fetch from <Object Name>; if you have used the Account object, the task name is auto populated as Fetch from Account (if you do not provide a Task name).
Note: Output Dataset Name auto populates from Task Name and it can be changed to different name. It has no dependency on Task Name.
In this use case, the following details are used:
- Task Name: Fetch from usage data [Maximum 80 characters and should be Alphanumeric; _ and space are supported]
- Task Description: Usage data fetch [ Maximum 200 characters]
- Output Dataset Name: Usage Data [Maximum 60 characters and should be Alphanumeric; _ and space are supported]. This gets pre-populated with the task name by default.
Matrix Data is the default Data source for all the Rules. For more information about the MDA objects and the fields used in Gainsight, refer <Gainsight Object Glossary> (TBA).
- Select Usage Data as the source object from Matrix Data. The fields available in the Usage Data object are displayed in the drop-down list.
Note: Usage Data is a Custom object. If you do not find this Object in the Objects list, you have to create the Object. Refer the Gainsight Data Management article to learn how to create, Custom Objects, Custom fields, and insert data into Custom fields.
- Drag and drop the following fields from Usage Data in the Show section:
- Drag and drop fields in the Filters section and apply logic as required. Advanced logic AND is applied on the selected filters automatically in the Advanced Logic section. You can modify the logical operator to OR. Advanced Logic is not case-sensitive in Setup Rule.
- Click SAVE to create the task as configured. This task is now available for you to proceed further. You can also click PREVIEW to view the task results in a new window. To navigate back to Tasks list, click <- icon.
The following are the limitations in task creation:
|Max # of tasks allowed||15|
|Max # of Show fields in each task||50||In Pivot task, we can pivot on a field using 200 cases|
|Max # of Group by fields in transformation tasks||10|
|Max # of filters allowed in each task||26||This limit is in filters of every task.|
|Max # of results displayed in Preview Results||100|
Fetch Data from S3 Bucket
Gainsight allows you to import data from Amazon S3 bucket. A S3 dataset task is specifically designed to configure and fetch data from Amazon S3 bucket. The source files can be stored in Gainsight bucket or any of your custom bucket. To learn more about, creating S3 Dataset tasks, refer the S3 Dataset in Rules Engine article.
You can also perform Transformation Tasks in Rules Engine. Transformation tasks supported in Rules Engine include Merge, Transformation, and Pivot. Group by Date and DateTime includes various functions at Day, Week, Month, Quarter, and Year. You can add Date field in the GroupBy section in any of the Transformation tasks (Aggregate/Pivot). For more information about custom grouping, refer to the <<Custom Grouping, Time Series, and Pivoting article>>(TBA). For more information about how you can transform data into a polished, actionable dataset in Rules Engine using the Merge, Pivot, and Transformation options, refer the following articles.