100%합격보장가능한Agentforce-Specialist덤프데모문제다운인증공부자료
힘든Salesforce Agentforce-Specialist시험패스도 간단하게 ! Itexamdump의 전문가들은Salesforce Agentforce-Specialist 최신시험문제를 연구하여 시험대비에 딱 맞는Salesforce Agentforce-Specialist덤프를 출시하였습니다. Itexamdump덤프를 구매하시면 많은 정력을 기울이지 않으셔도 시험을 패스하여 자격증취득이 가능합니다. Itexamdump의 Salesforce Agentforce-Specialist덤프로 자격증 취득의 꿈을 이루어보세요.
Salesforce Agentforce-Specialist 시험요강:
주제
소개
주제 1
주제 2
주제 3
주제 4
주제 5
>> Agentforce-Specialist덤프데모문제 다운 <<
Salesforce Agentforce-Specialist퍼펙트 덤프데모문제 - Agentforce-Specialist합격보장 가능 인증덤프
Itexamdump에서는 Salesforce인증 Agentforce-Specialist시험을 도전해보시려는 분들을 위해 퍼펙트한 Salesforce인증 Agentforce-Specialist덤프를 가벼운 가격으로 제공해드립니다.덤프는Salesforce인증 Agentforce-Specialist시험의 기출문제와 예상문제로 제작된것으로서 시험문제를 거의 100%커버하고 있습니다. Itexamdump제품을 한번 믿어주시면 기적을 가져다 드릴것입니다.
최신 AI Specialist Agentforce-Specialist 무료샘플문제 (Q168-Q173):
질문 # 168
In the context of retriever and search indexes, what best describes the data preparation process in Data Cloud?
정답：A
설명：
Why is "Loading, Chunking, Vectorizing, and Storing" the correct answer?
Agentforce AI-powered search and retriever indexing requires data to be structured and optimized for retrieval. The Data Cloud preparation process involves:
Key Steps in the Data Preparation Process for Agentforce:
* Loading Data
* Raw text from documents, emails, chat transcripts, and Knowledge articles is loaded into Data Cloud.
* Chunking (Breaking Text into Small Parts)
* AI divides long-form text into retrievable chunks to improve response accuracy.
* Example: A 1000-word article might be split into multiple indexed paragraphs.
* Vectorization (Transforming Text for AI Retrieval)
* Each text chunk is converted into numerical vector embeddings.
* This enables faster AI-powered searches based on semantic meaning, not just keywords.
* Storing in a Vector Database
* The processed data is stored in a search-optimized vector format.
* Agentforce AI retrievers use this data to find relevant responses quickly.
Why Not the Other Options?
# A. Real-time data ingestion and dynamic indexing
* Incorrect because while real-time updates can occur, the primary process involves preprocessing and indexing first.
# B. Aggregating, normalizing, and encoding structured datasets
* Incorrect because this process relates to data compliance and security, not AI retrieval optimization.
Agentforce Specialist References
* Salesforce AI Specialist Material confirms that data preparation includes chunking, vectorizing, and storing for AI retrieval in Data Cloud.
질문 # 169
When a customer chat is initiated, which functionality in Salesforce provides generative AI replies or draft emails based on recommended Knowledge articles?
정답：C
설명：
When acustomer chat is initiated,Einstein Service Repliesprovidesgenerative AI replies or draft emails based on recommendedKnowledge articles. This feature uses the information from theSalesforce Knowledge baseto generate responses that are relevant to the customer's query, improving the efficiency and accuracy of customer support interactions.
* Option Bis correct becauseEinstein Service Repliesis responsible for generating AI-driven responses based on knowledge articles.
* Option A(Einstein Reply Recommendations) is focused on recommending replies but does not generate them.
* Option C(Einstein Grounding) refers to grounding responses in data but is not directly related to drafting replies.
:
Einstein Service Replies Overview:https://help.salesforce.com/s/articleView?id=sf.einstein_service_replies.
htm
질문 # 170
Universal Containers' sales team engages in numerous video sales calls with prospects across the nation. Sales management wants an easy way to understand key information such as deal terms or customer sentiments.
Which Einstein Generative AI feature should An Agentforce recommend for this request?
정답：A
설명：
Einstein Call Summaries is the best option for this scenario because it leverages Salesforce's AI capabilities to automatically summarize key details of video or voice calls. It includes details like deal terms, customer sentiments, follow-up tasks, and other crucial information. This feature is designed to help sales teams focus on their strategies rather than taking extensive manual notes during conversations.
* Einstein Call Summaries:Automatically generates summaries for calls, identifying critical points such as next steps and follow-ups, enhancing efficiency and understanding of deal progression.
* Einstein Conversation Insights:While it provides insights into customer sentiment and engagement, it is more suited for analyzing patterns across conversations rather than summarizing specific call details.
* Einstein Video KPI:Focuses on analyzing key performance indicators within video calls but does not offer summarization features needed for deal terms or sentiment tracking.
This feature ensures actionable insights are delivered directly into the Salesforce CRM, allowing sales managers to gain a concise overview without manually reviewing long recordings.
질문 # 171
Universal Containers is using Agentforce for Sales to find similar opportunities to help close deals faster. The team wants to understand the criteria used by the Agent to match opportunities. What is one criterion that Agentforce for Sales uses to match similar opportunities?
정답：C
설명：
Comprehensive and Detailed In-Depth Explanation:
UC uses Agentforce for Sales to identify similar opportunities, aiding deal closure. Let's determine a criterion used by the "Find Similar Opportunities" feature.
* Option A: Matched opportunities have a status of Closed Won from the last 12 months.Agentforce for Sales analyzes historical data to find similar opportunities, prioritizing "Closed Won" deals as successful examples. Documentation specifies a 12-month lookback period for relevance, ensuring recent, applicable matches. This is a key criterion, making it the correct answer.
* Option B: Matched opportunities are limited to the same account.While account context may factor in, Agentforce doesn't restrict matches to the same account-it considers broader patterns across opportunities (e.g., industry, deal size). This is too narrow and incorrect.
* Option C: Matched opportunities were created in the last 12 months.Creation date isn't a primary criterion-status (e.g., Closed Won) and recency of closure matter more. This doesn't align with documented behavior, making it incorrect.
Why Option A is Correct:
"Closed Won" status within 12 months is a documented criterion for Agentforce's similarity matching, providing actionable insights for deal closure.
References:
Salesforce Agentforce Documentation: Agentforce for Sales > Find Similar Opportunities- Specifies Closed Won, 12-month criterion.
Trailhead: Explore Agentforce Sales Agents- Details opportunity matching logic.
Salesforce Help: Sales Features in Agentforce- Confirms historical success focus.
질문 # 172
Universal Containers wants to reduce overall customer support handling time by minimizing the time spent typing routine answers for common questions in-chat, and reducing the post-chat analysis by suggesting values for case fields. Which combination of Agentforce for Service features enables this effort?
정답：C
설명：
Comprehensive and Detailed In-Depth Explanation:
Universal Containers (UC) aims to streamline customer support by addressing two goals: reducing in-chat typing time for routine answers and minimizing post-chat analysis by auto-suggesting case field values. In Salesforce Agentforce for Service,Einstein Reply RecommendationsandCase Classification(Option A) are the ideal combination to achieve this.
* Einstein Reply Recommendations: This feature uses AI to suggest pre-formulated responses based on chat context, historical data, and Knowledge articles. By providing agents with ready-to-use replies for common questions, it significantly reduces the time spent typing routine answers, directly addressing UC's first goal.
* Case Classification: This capability leverages AI to analyze case details (e.g., chat transcripts) and suggest values for case fields (e.g., Subject, Priority, Resolution) during or after the interaction. By automating field population, it reduces post-chat analysis time, fulfilling UC's second goal.
* Option B: While "Einstein Reply Recommendations" is correct for the first part, "Case Summaries" generates a summary of the case rather than suggesting specific field values. Summaries are useful for documentation but don't directly reduce post-chat field entry time.
* Option C: "Einstein Service Replies" is not a distinct, documented feature in Agentforce (possibly a distractor for Reply Recommendations), and "Work Summaries" applies more to summarizing work orders or broader tasks, not case field suggestions in a chat context.
* Option A: This combination precisely targets both in-chat efficiency (Reply Recommendations) and post-chat automation (Case Classification).
Thus, Option A is the correct answer for UC's needs.
:
Salesforce Agentforce Documentation: "Einstein Reply Recommendations" (Salesforce Help:https://help.
salesforce.com/s/articleView?id=sf.einstein_reply_recommendations.htm&type=5) Salesforce Agentforce Documentation: "Case Classification" (Salesforce Help:https://help.salesforce.com/s
/articleView?id=sf.case_classification.htm&type=5)
Trailhead: "Agentforce for Service" (https://trailhead.salesforce.com/content/learn/modules/agentforce-for- service)
질문 # 173
......
Itexamdump의Salesforce Agentforce-Specialist 인증시험덤프는 자주 업데이트 되고, 오래 되고 더 이상 사용 하지 않는 문제들은 바로 삭제해버리며 새로운 최신 문제들을 추가 합니다. 이는 응시자가 확실하고도 빠르게Salesforce Agentforce-Specialist덤프를 마스터하고Salesforce Agentforce-Specialist시험을 패스할수 있도록 하는 또 하나의 보장입니다. 매력만점Salesforce Agentforce-Specialist덤프 강력 추천합니다.
Agentforce-Specialist퍼펙트 덤프데모문제: https://www.itexamdump.com/Agentforce-Specialist.html