QUESTION: 41

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?

Predict customer sentiment toward a promotion message.
Predict customer lifetime value of an account.
Predict most popular products from new product catalog.

Answer(s): B

Explanation:

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.

Reference:

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

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QUESTION: 42

An AI Specialist at Universal Containers is working on a prompt template to generate personalized emails for product demonstration requests from customers. It is important for the Al-generated email to adhere strictly to the guidelines, using only associated opportunity information, and to encourage the recipient to take the desired action.
How should the AI Specialist include these instructions on a new line in the prompt template?

Surround them with triple quotes (""").
Make sure merged fields are defined.
Use curly brackets {} to encapsulate instructions.

Answer(s): A

Explanation:

In Salesforce prompt templates, instructions that guide how the Large Language Model (LLM) should generate content (in this case, personalized emails) can be included by surrounding the instruction text with triple quotes ("""). This formatting ensures that the LLM adheres to the specific instructions while generating the email content.
The use of triple quotes allows the AI to understand that the enclosed text is a directive for how to approach the task, such as limiting the content to associated opportunity information or encouraging a specific action from the recipient.
Refer to Salesforce Prompt Builder documentation for detailed instructions on how to structure prompts for generative AI.

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QUESTION: 43

Universal Containers implements Custom Copilot Actions to enhance its customer service operations. The development team needs to understand the core components of a Custom Copilot Action to ensure proper configuration and functionality.
What should the development team review in the Custom Copilot Action configuration to identify one of the core components of a Custom Copilot Action?

Instructions
Output Types
Action Triggers

Answer(s): B

Explanation:

Universal Containers is enhancing its customer service operations with Custom Copilot Actions. The development team needs to understand the core components of a Custom Copilot Action to ensure proper configuration and functionality. One of these core components is the Output Types.

Core Components of a Custom Copilot Action:
Instructions:
Defines what the action should accomplish.
Provides guidance to the AI assistant on how to execute the action.
Input Parameters:
The data inputs required for the action to perform its task. Specifies the parameters that users or systems need to provide.
Output Types:
Definition: Specifies the type of data the action will output after execution.

Importance: Ensures that the Copilot and other components understand the format and structure of the action's results.
Examples: Text, JSON, records, or other data structures.
Action

Reference:

Points to the underlying implementation, such as an Apex class or Flow.
Action Triggers:
Conditions or events that initiate the action.
Focus on Output Types:
Relevance in Configuration:
The development team must define the Output Types correctly to ensure that the action's results are properly processed and displayed by Copilot.
Incorrect or undefined Output Types can lead to misinterpretation of data and failures in functionality.
Why Output Types are a Core Component:
Integration with Copilot:
Copilot relies on the Output Types to understand how to handle the data returned by the action.
Data Consistency:
Defines the structure and format of the output, ensuring consistent communication between the action and Copilot.
User Experience:
Proper Output Types ensure that users receive the expected results in an understandable format.
Why Other Options are Less Suitable:
Option A (Instructions):
While Instructions are a core component, the question asks for what should be reviewed in the configuration to identify one of the core components.
In this context, reviewing Output Types is more critical to ensuring proper configuration and functionality.
Option C (Action Triggers):
Action Triggers are important but are not always considered a core component within the configuration of a Custom Copilot Action.
Triggers often relate to when an action is initiated rather than the configuration of the action itself.

Salesforce AI Specialist Documentation - Custom Copilot Actions:
Details the components and configuration of Custom Copilot Actions. Salesforce Help - Defining Output Types in Custom Actions:
Explains the importance of Output Types and how to configure them. Salesforce Trailhead - Building Custom Copilot Actions:
Provides a hands-on approach to creating and configuring Custom Copilot Actions, highlighting key components.

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QUESTION: 44

Based on the user utterance, "Show me all the customers in New York", which standard Einstein Copilot action will the planner service use?

Query Records
Select Records
Fetch Records

Answer(s): A

Explanation:

The standard Einstein Copilot action that would be used in response to the user utterance, "Show me all the customers in New York," is Query Records. This action is responsible for retrieving a set of records from Salesforce based on a specified condition -- in this case, filtering customers by location (New York).
Query Records is the action that fetches relevant data based on the criteria provided in the user's input.
Select Records is more about picking specific records from an already presented list. Fetch Records is not a standard term used in this context for the action.

Refer to Einstein Copilot documentation on how Copilot actions work with natural language queries and data retrieval.

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Free Salesforce-AI-Specialist Exam Braindumps (page: 11)

QUESTION: 41

Explanation:

Reference:

QUESTION: 42

Explanation:

QUESTION: 43

Explanation:

Reference:

QUESTION: 44

Explanation: