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Salesforce Exam Salesforce AI Specialist Topic 3 Question 7 Discussion

Actual exam question for Salesforce's Salesforce AI Specialist exam
Question #: 7
Topic #: 3
[All Salesforce AI Specialist Questions]

Universal Containers Is Interested In Improving the sales operation efficiency by analyzing their data using Al-powered predictions in Einstein Studio.

Which use case works for this scenario?

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Suggested Answer: B

For improving sales operations efficiency, Einstein Studio is ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predicting customer lifetime value, which helps sales teams focus on high-value accounts and make more informed decisions. Customer lifetime value (CLV) predictions can optimize strategies around customer retention, cross-selling, and long-term engagement.

Option B is the correct choice as predicting customer lifetime value is a well-established use case for AI in sales.

Option A (customer sentiment) is typically handled through NLP models, while Option C (product popularity) is more of a marketing analysis use case.


Salesforce Einstein Studio Use Case Overview: https://help.salesforce.com/s/articleView?id=sf.einstein_studio_overview

Contribute your Thoughts:

Buddy
7 days ago
Predicting customer sentiment towards a promotion message could be insightful, but I'm not sure that directly addresses the goal of improving sales operation efficiency.
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Dominque
18 days ago
I think option A could also be useful to understand customer sentiment and tailor promotions accordingly.
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Ocie
18 days ago
I think predicting customer lifetime value would be the most useful for improving sales efficiency. Knowing which customers are most valuable can help target resources and improve retention.
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Elly
11 days ago
B) Predict customer lifetime value of an account.
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Cecily
19 days ago
I agree with Wilbert, predicting customer lifetime value can help in targeting high-value accounts.
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Wilbert
22 days ago
I think option B makes sense for improving sales operation efficiency.
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