Agentforce-Specialist熱門證照 & Agentforce-Specialist題庫最新資訊
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最新的 AI Specialist Agentforce-Specialist 免費考試真題 (Q137-Q142):
問題 #137
The marketing team at Universal Containers is looking for a way personalize emails based on customer behavior, preferences, and purchase history.
Why should the team use Einstein Copilot as the solution?
答案：C
解題說明：
Einstein Copilotis designed to assist in generating personalized, AI-driven content based on customer data such as behavior, preferences, and purchase history. For the marketing team atUniversal Containers, this is the perfect solution to create dynamic and relevant email content. By leveragingEinstein Copilot, they can ensure that each customer receives tailored communications, improving engagement and conversion rates.
* Option Ais correct asEinstein Copilothelps generate real-time, personalized content based on comprehensive data about the customer.
* Option Brefers more to Einstein Analytics or
* Marketing Cloud Intelligence, andOption Cdeals with automation, which isn't the primary focus of Einstein Copilot.
References:
* Salesforce Einstein Copilot Overview:https://help.salesforce.com/s/articleView?
id=einstein_copilot_overview.htm
問題 #138
Universal Containers' current AI data masking rules do not align with organizational privacy and security policies and requirements.
What should An Agentforce recommend to resolve the issue?
答案：C
解題說明：
When Universal Containers' AI data masking rules do not meet organizational privacy and security standards, the Agentforce Specialist should configure the data masking rules within the Einstein Trust Layer. The Einstein Trust Layer provides a secure and compliant environment where sensitive data can be masked or anonymized to adhere to privacy policies and regulations.
* Option A, enabling data masking for sandbox refreshes, is related to sandbox environments, which are separate from how AI interacts with production data.
* Option C, adding masking rules in the LLM setup, is not appropriate because data masking is managed through the Einstein Trust Layer, not the LLM configuration.
The Einstein Trust Layer allows for more granular control over what data is exposed to the AI model and ensures compliance with privacy regulations.
Salesforce Agentforce Specialist References:
For more information, refer to: https://help.salesforce.com/s/articleView?id=sf.
einstein_trust_layer_data_masking.htm
問題 #139
Universal Containers wants to allow its service agents to query the current fulfillment status of an order with natural language. There is an existing auto launched flow to query the information from Oracle ERP, which is the system of record for the order fulfillment process.
How should An Agentforce apply the power of conversational AI to this use case?
答案：A
解題說明：
To enableUniversal Containersservice agents to query the current fulfillment status of an order using natural language and leverage an existing auto-launched flow that queries Oracle ERP, the best solution is tocreate a custom copilot action that calls the flow. This action will allowAgentto interact with the flow and retrieve the required order fulfillment information seamlessly. Custom copilot actions can be tailored to call various backend systems or flows in response to user requests.
* Option Bis correct because it enables integration betweenAgentand the flow that connects to Oracle ERP.
* Option A(Flex prompt template) is more suited for static responses and not for invoking flows.
* Option C(Integration Flow Standard Action) is not directly related to creating a specific copilot action for this use case.
:
Salesforce Agent Actions:https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm
問題 #140
Universal Containers plans to enhance its sales team's productivity using AI. Which specific requirement necessitates the use of Prompt Builder?
答案：A
解題說明：
Comprehensive and Detailed In-Depth Explanation:
UC seeks an AI solution for sales productivity. Let's determine which requirement aligns with Prompt Builder.
* Option A: Creating a draft newsletter for an upcoming tradeshow.Prompt Builder excels at generating text outputs (e.g., newsletters) using Generative AI. UC can create a prompt template to draft personalized, context-rich newsletters based on sales data, boosting productivity. This matches Prompt Builder's capabilities, making it the correct answer.
* Option B: Predicting the likelihood of customers churning or discontinuing their relationship with the company.Churn prediction is a predictive AI task, suited for Einstein Prediction Builder or Data Cloud models, not Prompt Builder, which focuses on generative tasks. This is incorrect.
* Option C: Creating an estimated Customer Lifetime Value (CLV) with historical purchase data.
CLV estimation involves predictive analytics, not text generation, and is better handled by Einstein Analytics or custom models, not Prompt Builder. This is incorrect.
Why Option A is Correct:
Drafting newsletters is a generative task uniquely suited to Prompt Builder, enhancing sales productivity as per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Prompt Builder > Use Cases- Lists text generation like newsletters.
Trailhead: Build Prompt Templates in Agentforce- Covers productivity-enhancing text outputs.
Salesforce Help: Generative AI with Prompt Builder- Confirms drafting capabilities.
問題 #141
Universal Containers needs to provide insights on the usability of Agents to drive adoption in the organization.
What should theAgentforce Specialistrecommend?
答案：B
解題說明：
* Agent Analytics: This tool is specifically designed to provide usability insights for Salesforce agents. It tracks metrics like adoption rates, task completion times, and efficiency levels, helping organizations identify areas where agents excel or need additional support.
* Agentforce Analytics: This term does not correspond to a recognized Salesforce feature.
* Agent Studio Analytics: This is unrelated to analyzing agent usability, as it primarily supports customization or development features rather than providing analytics for adoption.
Thus,Agent Analyticsis the correct recommendation as it offers actionable insights to drive agent adoption and productivity.
問題 #142
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