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Salesforce Certified AI Specialist Exam Sample Questions (Q86-Q91):
NEW QUESTION # 86
Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. The goal is to enhance the team's performance by identifying areas for improvement and competitive intelligence.
Which feature provides insights about competitor mentions and coaching opportunities?
- A. Call Explorer
- B. Call Summaries
- C. Einstein Sales Insights
Answer: A
Explanation:
For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information, Call Explorer is the most suitable feature. Call Explorer, a part of Einstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentions and moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls.
Call Summaries offer a quick overview of a call but do not delve deep into competitor mentions or coaching insights.
Einstein Sales Insights focuses more on pipeline and forecasting insights rather than call-based analysis.
Reference:
Salesforce Einstein Conversation Insights Documentation: https://help.salesforce.com/s/articleView?id=einstein_conversation_insights.htm
NEW QUESTION # 87
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 AI Specialist apply the power of conversational AI to this use case?
- A. Create a custom copilot action which calls a flow.
- B. Configure the Integration Flow Standard Action in Einstein Copilot.
- C. Create a Flex prompt template in Prompt Builder.
Answer: A
Explanation:
To enable Universal Containers service 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 to create a custom copilot action that calls the flow. This action will allow Einstein Copilot to 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 B is correct because it enables integration between Einstein Copilot and 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.
Reference:
Salesforce Einstein Copilot Actions: https://help.salesforce.com/s/articleView?id=einstein_copilot_actions.htm
NEW QUESTION # 88
A data science team has trained an XGBoost classification model for product recommendations on Databricks. The AI Specialist is tasked with bringing inferences for product recommendations from this model into Data Cloud as a stand-alone data model object (DMO).
How should the AI Specialist set this up?
- A. Create the serving endpoint in Einstein Studio, then configure the model using Model Builder.
- B. Create the serving endpoint in Databricks, then configure the model using Model Builder.
- C. Create the serving endpoint in Databricks, then configure the model using a Python SDK connector.
Answer: B
Explanation:
To integrate inferences from an XGBoost model into Salesforce's Data Cloud as a stand-alone Data Model Object (DMO):
* Create the Serving Endpoint in Databricks:
* The serving endpoint is necessary to make the trained model available for real-time inference.
Databricks provides tools to host and expose the model via an endpoint.
* Configure the Model Using Model Builder:
* After creating the endpoint, the AI Specialist should configure it within Einstein Studio's Model Builder, which integrates external endpoints with Salesforce Data Cloud for processing and storing inferences as DMOs.
* Option B: Serving endpoints are not created in Einstein Studio; they are set up in external platforms like Databricks before integration.
* Option C: A Python SDK connector is not used to bring model inferences into Salesforce Data Cloud; Model Builder is the correct tool.
NEW QUESTION # 89
Universal Containers is planning a marketing email about products that most closely match a customer's expressed interests.
What should an AI Specialist recommend to generate this email?
- A. Custom sales email template which is grounded with interest and product information
- B. Standard email draft with Einstein and choose standard email template
- C. Standard email marketing template using Apex or flows for matching interest in products
Answer: A
Explanation:
To generate an email about products that closely match a customer's expressed interests, an AI Specialist should recommend using acustom sales email templatethat isgrounded with interest and product information. This ensures that the email content is personalized based on the customer's preferences, increasing the relevance of the marketing message.
Using grounding ensures that the generative AI pulls the correct data related to customer interests and product matches, making the email more effective.
For more information, refer toSalesforce documentationon grounding AI-generated content and email personalization strategies.
NEW QUESTION # 90
Universal Containers needs a tool that can analyze voice and video call records to provide insights on competitor mentions, coaching opportunities, and other key information. Thegoal is to enhance the team'sperformance by identifying areas for improvement and competitive intelligence.
Which feature provides insights about competitor mentions and coaching opportunities?
- A. Call Explorer
- B. Call Summaries
- C. Einstein Sales Insights
Answer: A
Explanation:
For analyzing voice and video call records to gain insights into competitor mentions, coaching opportunities, and other key information,Call Exploreris the most suitable feature.Call Explorer, a part ofEinstein Conversation Insights, enables sales teams to analyze calls, detect patterns, and identify areas where improvements can be made. It uses natural language processing (NLP) to extract insights, including competitor mentionsand moments for coaching. These insights are vital for improving sales performance by providing a clear understanding of the interactions during calls.
* Call Summariesoffer a quick overview of a call but do not delve deep into competitor mentions or coaching insights.
* Einstein Sales Insightsfocuses more on pipeline and forecasting insights rather than call-based analysis.
References:
* Salesforce Einstein Conversation Insights Documentation:https://help.salesforce.com/s/articleView?
id=einstein_conversation_insights.htm
NEW QUESTION # 91
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