さらに、CertShiken Agentforce-Specialistダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1PtzIxAloPjq3DwFZrJFgX9EzPwtoFuI7
Agentforce-Specialist試験資料は試験に緊密に関連しています。あなたAgentforce-Specialist試験資料を勉強したら、その資料のメリットを見つけることができます。Agentforce-Specialist試験資料の問題の答えを覚えると、試験に合格する可能性が大きいです。使い安ク、便利で、全面的で、全部Agentforce-Specialist試験資料の特徴です。だから、Agentforce-Specialist試験資料は有難い商品です。
| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Agentforce Specialist (AI-201) |
| Exam Number: | AI-201 |
| Exam Duration: | 105 minutes |
| Exam Price: | USD 200 |
| Related Certifications: | Salesforce Platform Administrator Salesforce AI Associate (retired) Salesforce Platform App Builder Salesforce AI Specialist (retired) |
| Available Languages: | French, Japanese, English |
| Real Exam Qty: | 60 multiple-choice questions + up to 5 unscored questions |
| Passing Score: | 72%-73% |
| Exam Format: | Scenario-based Questions, Multiple Choice, Multiple Select |
| Recommended Training: | Agentforce Specialist Exam Prep Salesforce Trailhead Agentforce Learning Paths |
| Exam Registration: | Salesforce Certification Registration Certification Exam Guide |
| Sample Questions: | Salesforce Agentforce-Specialist Sample Questions |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | None |
| Official Syllabus URL: | https://help.salesforce.com/s/articleView?id=005298924&type=1 |
>> Agentforce-Specialist試験関連赤本 <<
CertShikenクライアントにAgentforce-Specialist学習資料の3つのバージョンを提供し、PDFバージョン、PCバージョン、APPオンラインバージョンが含まれます。 異なるバージョンは、Salesforce独自の利点とメソッドの使用を後押しします。 Agentforce-Specialist試験トレントの内容は同じですが、クライアントごとに異なるバージョンが適しています。 たとえば、PCバージョンのAgentforce-Specialist学習教材は、Windowsシステムを搭載したコンピューターをサポートします。その利点には、実際の操作試験環境をシミュレートし、試験をシミュレートでき、期間限定試験に参加できることです。 そして、バージョンが何であれ、ユーザーは自分の喜びでAgentforce-SpecialistのSalesforce Certified Agentforce Specialist (AI-201)ガイド急流を学ぶことができます。 タイトルと回答は同じであり、コンピューターまたは携帯電話またはラップトップで製品を使用できます。
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質問 # 169
Universal Containers is interested in using Call Explorer to quickly gain insights from meetings recorded by its sales team.
What should the Agentforce Specialist be aware of before enabling this feature?
正解：C
解説：
Before enabling Call Explorer, the Salesforce Agentforce Specialist must ensure that the Einstein Conversation Insights permission set is assigned to users (Option C). Call Explorer is a feature within Einstein Conversation Insights (ECI) that analyzes meeting recordings to surface trends, keywords, and actionable insights.
Key Considerations:
* Permission Set Requirement:
* Users (including admins) need the Einstein Conversation Insights permission set to access and use Call Explorer.Without this, the feature remains inaccessible.
* The permission set grants access to ECI tools, including call transcription, analysis, and dashboard visibility.
* Why Other Options Are Incorrect:
* A. Independence from Salesforce Knowledge: While Call Explorer does not rely on Salesforce Knowledge, this is irrelevant to the setup prerequisite. The critical dependency is the permission set, not Knowledge configuration.
* B. Custom Actions: Call Explorer does not require custom actions to be built before configuration. It is a pre-built analytics tool that works once permissions and data sources (e.g., call recordings) are configured.
:
Salesforce Einstein Conversation Insights Guide: Explicitly states that the Einstein Conversation Insights permission set is required to access Call Explorer.
Trailhead Module: "Einstein Conversation Insights Basics" outlines permission prerequisites for enabling call analytics.
Salesforce Help Documentation: Confirms that Call Explorer functionality is governed by ECI permissions.
質問 # 170
An Agentforce Specialist is tasked with analyzing Agent interactions, looking into user inputs, requests, and queries to identify patterns and trends. What functionality allows the Agentforce Specialist to achieve this?
正解：B
解説：
Comprehensive and Detailed In-Depth Explanation:
The task requires analyzinguser inputs, requests, and queriesto identify patterns and trends in Agentforce interactions. Let's assess the options based on Agentforce's analytics capabilities.
* Option A: Agent Event Logs dashboard.Agent Event Logs capture detailed technical events (e.g., API calls, errors, or system-level actions) related to agent operations. While useful for troubleshooting or monitoring system performance, they are not designed to analyze user inputs or conversational trends. This option does not meet the requirement and is incorrect.
* Option B: AI Audit and Feedback Data dashboard.There's no specific "AI Audit and Feedback Data dashboard" in Agentforce documentation. Feedback mechanisms exist (e.g., user feedback on responses), and audit trails may track changes, but no single dashboard combines these for analyzing user queries and trends. This option appears to be a misnomer and is incorrect.
* Option C: User Utterances dashboard.The User Utterances dashboard in Agentforce Analytics is specifically designed to analyze user inputs, requests, and queries. It aggregates and visualizes what users are asking the agent, identifying patterns (e.g., common topics) and trends (e.g., rising query types). Specialists can use this to refine agent instructions or topics, making it the perfect tool for this task. This is the correct answer per Salesforce documentation.
Why Option C is Correct:
The User Utterances dashboard is tailored for conversational analysis, offering insights into user interactions that align with the specialist's goal of identifying patterns and trends. It's a documented feature of Agentforce Analytics for post-deployment optimization.
References:
Salesforce Agentforce Documentation: Agent Analytics > User Utterances Dashboard- Describes its use for analyzing user queries.
Trailhead: Monitor and Optimize Agentforce Agents- Highlights the dashboard's role in trend identification.
Salesforce Help: Agentforce Dashboards- Confirms User Utterances as a key tool for interaction analysis.
質問 # 171
An Agentforce Specialist is evaluating an agent conversation.
What is the reason why intents and session metrics within Observability are important to consider?
正解：B
解説：
The correct answer is A. Intents and session metrics in Agentforce Observability are broad operational indicators used to evaluate overall agent performance. They help specialists understand how often the agent is used, what users are trying to accomplish, how sessions progress, and whether the agent is producing effective outcomes. Option B is too narrow because diagnosing why a specific question was not answered requires deeper session tracing or inspection, not just high-level intent and session metrics. Option C is also too narrow because deflection rate is only one business outcome, while Observability metrics cover broader performance, behavior, and effectiveness. Salesforce describes Agentforce Observability as a way to analyze usage, effectiveness, feedback, and performance across deployed agents.
質問 # 172
Universal Containers wants an AI agent to answer questions about warranties using unstructured data stored in Data Cloud. Results must be filterable by product line and ranked by recent updates.
正解：A
解説：
Comprehensive and Detailed Explanation From Exact Extract:
The guide on RAG and search indexes indicates that if you need fine#tuned retrieval behaviour (such as filtering by product line and ranking by recency), you should build a custom retriever. The documentation states: "You can add ranking factors such as recency and popularity at the time of index creation ... Use pre#filter fields and ranking factors." Also: "When you create a search index, Data 360 automatically creates a default retriever ... you can create custom retrievers in Einstein Studio to refine search criteria." Hence to satisfy filtering by product line and recency ranking, the correct answer is B. Option A (default retriever) does not guarantee the filter/ranking customization; Option C (semantic embeddings with default metadata filters) may offer some filter capability but doesn't explicitly provide ranking by recency and fine filter by product line. Thus B is correct.
質問 # 173
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?
正解：B
解説：
For improvingsales operations efficiency,Einstein Studiois ideal for creating AI-powered models that can predict outcomes based on data. One of the most valuable use cases is predictingcustomer 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 Bis 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, whileOption C(product popularity) is more of a marketing analysis use case.
References:
Salesforce Einstein Studio Use Case Overview:https://help.salesforce.com/s/articleView?id=sf.
einstein_studio_overview
質問 # 174
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