Universal Containers (UC) noticed an increase in customer contract cancellations in the last few months. UC is seeking ways to address this issue by implementing a proactive outreach program to…

The correct answer is B. Customer churn prediction. Customer churn prediction uses a machine learning model to score existing customers on their likelihood of canceling or leaving, enabling proactive outreach before cancellation occurs-exactly what UC requires. Model Builder can train and deploy this type of classification model…

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Question

Universal Containers (UC) noticed an increase in customer contract cancellations in the last few months. UC is seeking ways to address this issue by implementing a proactive outreach program to customers before they cancel their contracts and is asking the Salesforce team to provide suggestions. Which use case functionality of Model Builder aligns with UC's request?

Options

AProduct recommendation prediction
BCustomer churn prediction
CContract Renewal Date prediction

How the community answered

(25 responses)

A
8% (2)
B
76% (19)
C
16% (4)

Explanation

Customer churn prediction uses a machine learning model to score existing customers on their likelihood of canceling or leaving, enabling proactive outreach before cancellation occurs-exactly what UC requires. Model Builder can train and deploy this type of classification model on Salesforce data. Product recommendation prediction (A) identifies what products to upsell or cross-sell, which does not address retention risk. Contract Renewal Date prediction (C) forecasts when a contract will be up for renewal (a regression/date task), but UC already knows the renewal dates; their problem is identifying which customers are at risk of not renewing, which is a churn classification problem.

Topics

#Customer Churn#Predictive Analytics#Salesforce Einstein#Customer Retention

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