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Salesforce Certified Agentforce Specialist Sample Questions (Q250-Q255):
NEW QUESTION # 250
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?
- A. Product recommendation prediction
- B. Customer churn prediction
- C. Contract Renewal Date prediction
Answer: B
Explanation:
Customer churn predictionis the best use case forModel Builderin addressingUniversal Containers' concerns about increasing customer contract cancellations. By implementing a model that predicts customer churn,UCcan proactively identify customers who are at risk of canceling and take action to retain them before they decide to terminate their contracts. This functionality allows the business to forecast churn probability based on historical data and initiate timely outreach programs.
* Option Bis correct becausecustomer churn predictionaligns withUC'sneed to reduce cancellations through proactive measures.
* Option A(product recommendation prediction) is unrelated to contract cancellations.
* Option C(contract renewal date prediction) addresses timing but does not focus on predicting potential cancellations.
:
Salesforce Model Builder Use Case Overview:https://help.salesforce.com/s/articleView?id=sf.
model_builder_use_cases.htm
NEW QUESTION # 251
A sales manager is using Agent Assistant to streamline their daily tasks. They ask the agent to Show me a list of my open opportunities.
How does the large language model (LLM) in Agentforce identify and execute the action to show the sales manager a list of open opportunities?
- A. The LLM uses a static set of rules to match the user's request with predefined topics and actions, bypassing the need for dynamic interpretation and planning.
- B. Using a dialog pattern. the LLM matches the user query to the available topic, action and steps thenperforms the steps for each action, such as retrieving a fast of open opportunities.
- C. The LLM interprets the user's request, generates a plan by identifying the apcMopnete topics and actions, and executes the actions to retrieve and display the open opportunities
Answer: C
Explanation:
Agentforce's LLM dynamically interprets natural language requests (e.g., "Show me open opportunities"), generates an execution plan using the planner service, and retrieves data via actions (e.g., querying Salesforce records). This contrasts with static rules (B) or rigid dialog patterns (C), which lack contextual adaptability.
Salesforce documentation highlights the planner's role in converting intents into actionable steps while adhering to security and business logic.
Reference:
Salesforce Help Article: Agentforce Planner Service ("Dynamic Request Interpretation" section).
Einstein Agentforce Specialist Trailhead: "How Agentforce Processes User Requests."
NEW QUESTION # 252
Which element in the Omni-Channel Flow should be used to connect the flow with the agent?
- A. Route Work Action
- B. Decision
- C. Assignment
Answer: A
Explanation:
Comprehensive and Detailed In-Depth Explanation:
UC is integrating an Agentforce agent with Omni-Channel Flow to route work. Let's identify the correct element.
* Option A: Route Work ActionThe "Route Work" action in Omni-Channel Flow assigns work items (e.
g., cases, chats) to agents or queues based on routing rules. When connecting to an Agentforce agent, this action links the flow to the agent's queue or presence, enabling interaction. This is the standard element for agent integration, making it the correct answer.
* Option B: AssignmentThere's no "Assignment" element in Flow Builder for Omni-Channel.
Assignment rules exist separately, but within flows, routing is handled by "Route Work," making this incorrect.
* Option C: DecisionThe "Decision" element branches logic, not connects to agents. It's a control structure, not a routing mechanism, making it incorrect.
Why Option A is Correct:
"Route Work" is the designated Omni-Channel Flow action for connecting to agents, including Agentforce agents, per Salesforce documentation.
References:
Salesforce Agentforce Documentation: Omni-Channel Integration- Specifies "Route Work" for agents.
Trailhead: Omni-Channel Flow Basics- Details routing actions.
Salesforce Help: Set Up Omni-Channel Flows- Confirms "Route Work" usage.
NEW QUESTION # 253
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?
- A. To generate relevant content when engaging with each customer
- B. To analyze past campaign performance
- C. To send automated emails to all customers
Answer: A
Explanation:
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
NEW QUESTION # 254
Universal Containers (UC) wants to improve the productivity of its sales team with generative AI technology.
However, UC is concerned that public AI virtual assistants lack adequate company data to general useful responses.
Which solution should UC consider?
- A. Build Al model with Einstein discovery and deploy to sales users.
- B. fine-tune the Einstein AI model with CBM data.
- C. Enable Agentforce and deploy to sales users.
Answer: B
Explanation:
* Context of the Question: Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.
* Why Fine-Tune an Einstein AI Model with CRM Data?
* Company-Specific Relevance: By fine-tuning Einstein AI with UC's CRM data (accounts, opportunities, products, and historical interactions), the model learns the enterprise-specific context. This ensures that the generative outputs are accurate and tailored to UC's sales scenarios.
* Security and Compliance: Using Salesforce Einstein within the Salesforce ecosystem keeps data under UC's control, aligning with trust, security, and compliance requirements.
* Better Predictions: Einstein AI can produce more relevant insights (e.g., recommended next steps, content suggestions, or AI-generated email responses) when it has been trained on real, high-quality internal data.
* Why Not Build an AI Model with Einstein Discovery (Option B)?
* Einstein Discovery Use Case: Einstein Discovery is best suited for predictive and prescriptive analytics (e.g., analyzing large data sets for patterns, scoring leads, or predicting churn). While it provides advanced analytics, it is not primarily designed for generative text-based interactions for end-user consumption in a conversational format.
* Why Not Enable Agentforce (Option C)?
* Agentforce Overview: "Agentforce" (sometimes referencing a pilot or non-mainstream name) typically focuses on interactive help or workforce collaboration. It does not inherently solve the problem of large-scale generative AI using internal CRM data. Moreover, you still need a robust generative engine fine-tuned on company data.
* Outcome: Fine-tuning the Einstein AI model with UC's CRM data (Answer A) is the most direct, Salesforce-native solution to provide generative AI responses that are aligned with UC's context, driving productivity gains and ensuring data privacy.
SalesforceAgentforce SpecialistReferences & Documents
* Salesforce Official: Einstein GPT Overview
* Discusses how Einstein GPT can be fine-tuned with specific CRM data to deliver contextually relevant, generative AI responses.
* Salesforce Trailhead:Get Started with Salesforce Einstein
* Explains the fundamentals of AI within the Salesforce platform, including training and optimizing Einstein models.
* Salesforce Documentation: Einstein Discovery
* Details how Einstein Discovery is primarily used for advanced analytics and predictions, not direct generative text solutions.
* SalesforceAgentforce SpecialistStudy Guide
* Provides the official outline of Einstein AI capabilities, referencing how to configure and fine- tune models for specialized enterprise use cases.
NEW QUESTION # 255
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