Create a CRM Analytics Template Configuration to Predict Vehicle and Part Warranty Claim
Approvals
Create and set up a template configuration in Scoring Framework to install a
customizable CRM Analytics app that generates predictions about the likelihood of vehicle and part
warranty claims getting approved.
Required Editions
Available in: Lightning Experience
Available in: Enterprise, Performance, and Unlimited
Editions
User Permissions Needed
To create a CRM Analytics template configuration:
Scoring Framework Admin
To install a CRM Analytics app:
Manage CRM Analytics Templated Apps
Note To get these predictions, you don’t need to select the prediction
duration and historical datasets. As a result, the Select Prediction Duration & CRM
Analytics Datasets step doesn’t appear when you select Warranty Claim Approval Score
(Manufacturing or Automotive Cloud) as the template configuration type.
In Scoring Framework, create a CRM Analytics template configuration that uses Warranty
Claim Approval Score (Manufacturing or Automotive Cloud) as the template configuration
type.
Select Claim as the object to train your model and get predictions
for.
To better analyze your data, include input features that are in a CRM Analytics
dataset.
Define the target variable for your model.
To define a predefined target variable, select Warranty Claim with 50
Percent Claimed Amount Approved or Warranty Claim with 70 Percent
Claimed Amount Approved.
To define a custom target variable, add conditions.
Select input features from a CRM Analytics dataset, a predefined set of fields, or from the
object that you selected for training and scoring.
To focus your predictions on a specific subset of the claims data, define filter
conditions.
To display your generated predictions in records, select a preconfigured output connector,
and then select one of these objects and its field to store the prediction.
Claim
Claim Coverage
Claim Coverage Payment Detail
Claim Item
Claim Participant
To show prediction scores, suggestions and insights about prediction scores, and Next Best
Action recommendations, create an AI Accelerator use case.
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