SALESFORCE AGENTFORCE-SPECIALIST LATEST TEST GUIDE | AGENTFORCE-SPECIALIST ASSOCIATE LEVEL EXAM

Salesforce Agentforce-Specialist Latest Test Guide | Agentforce-Specialist Associate Level Exam

Salesforce Agentforce-Specialist Latest Test Guide | Agentforce-Specialist Associate Level Exam

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Tags: Agentforce-Specialist Latest Test Guide, Agentforce-Specialist Associate Level Exam, Agentforce-Specialist New Test Camp, New Study Agentforce-Specialist Questions, Standard Agentforce-Specialist Answers

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Salesforce Agentforce-Specialist Exam Syllabus Topics:

TopicDetails
Topic 1
  • Prompt Engineering: This section measures the skills of AI Developers and focuses on prompt engineering techniques. It covers identifying when to use Prompt Builder, managing prompt templates, selecting appropriate grounding techniques, and explaining the process for creating and executing prompt templates.
Topic 2
  • Agentforce and Sales Cloud: This section assesses the skills of AI Developers and covers identifying the correct generative AI features in Agentforce for Sales Cloud scenarios. It also includes determining when to use Agentforce Sales Agents, such as Sales Development Representatives (SDRs) and Sales Coaches.
Topic 3
  • Agentforce Concepts: This section assesses the skills of AI Engineers and covers how Agentforce works, including its reasoning engine, standard and custom topics, agent actions, and user security management. It also includes testing and deploying agents from sandbox to production environments.
Topic 4
  • Agentforce and Service Cloud: This section measures the skills of AI Engineers and focuses on building agents that answer questions based on Knowledge articles and connecting them to digital channels. It also covers identifying the correct generative AI features in Agentforce for Service Cloud scenarios.
Topic 5
  • Agentforce and Data Cloud: This section measures the skills of AI Developers and addresses how Agentforce integrates with Data Cloud to improve response accuracy and personalize answers. It involves grounding with retrievers in Data Cloud to enhance agent performance.

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Agentforce-Specialist Latest Test Guide | High-quality Agentforce-Specialist: Salesforce Certified Agentforce Specialist

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Salesforce Certified Agentforce Specialist Sample Questions (Q104-Q109):

NEW QUESTION # 104
Which use case is best supported by Salesforce Einstein Copilot's capabilities?

  • A. Bring together a conversational interface for interacting with AI for all Salesforce users, such as developers and ecommerce retailers.
  • B. Enable data scientists to train predictive AI models with historical CRM data using built-in machine learning capabilities
  • C. Enable Salesforce admin users to create and train custom large language models (LLMs) using CRM data.

Answer: A

Explanation:
Salesforce Einstein Copilotis designed to provide a conversational AI interface that can be utilized by different types of Salesforce users, such as developers, sales agents, and retailers. It acts as anAI-powered assistantthat facilitates natural interactions with the system, enabling users to perform tasks and access data easily. This includes tasks like pulling reports, updating records, and generating personalized responses in real time.
* Option Ais correct becauseEinstein Copilotbrings a conversational interface that caters to a wide range of users.
* Option BandOption Care more focused on developing and training AI models, which are not the primary functions ofEinstein Copilot.
References:
* Salesforce Einstein Copilot Overview:https://help.salesforce.com/s/articleView?
id=einstein_copilot_overview.htm


NEW QUESTION # 105
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. Customer churn prediction
  • B. Contract Renewal Date prediction
  • C. Product recommendation prediction

Answer: A

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.
References:
* Salesforce Model Builder Use Case Overview:https://help.salesforce.com/s/articleView?id=sf.
model_builder_use_cases.htm


NEW QUESTION # 106
Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates.
Which type of flow should UC use?

  • A. Template-triggered prompt flow
  • B. Unified-object linking flow
  • C. Data Cloud-triggered flow

Answer: A

Explanation:
In this scenario,Universal Containerswants to bring data fromunified Data Cloud objectsinto prompt templates, and the best way to do that is through aData Cloud-triggered flow. This type of flow is specifically designed to trigger actions based on data changes within Salesforce Data Cloud objects.
Data Cloud-triggered flows can listen for changes in the unified data model and automatically bring relevant data into the system, making it available for prompt templates. This ensures that the data is both real-time and up-to-date when used in generative AI contexts.
For more detailed guidance, refer to Salesforce documentation onData Cloud-triggered flowsandData Cloud integrationswith generative AI solutions.


NEW QUESTION # 107
Before activating a custom copilot action, An Agentforce would like is to understand multiple real-world user utterances to ensure the action being selected appropriately.
Which tool should theAgentforce Specialistrecommend?

  • A. Model Playground
  • B. Einstein Copilot
  • C. Copilot Builder

Answer: C

Explanation:
To understand multiple real-world user utterances and ensure the correct action is selected before activating a custom copilot action, the recommended tool isCopilot Builder. This tool allowsAgentforce Specialists to design and test conversational actions in response to user inputs, helping ensure the copilot can accurately handle different user queries and phrases.Copilot Builderprovides the ability to test, refine, and improve actions based on real-world utterances.
* Option Cis correct asCopilot Builderis designed for configuring and testing conversational actions.
* Option A(Model Playground) is used for testing models, not user utterances.
* Option B(Einstein Copilot) refers to the conversational interface but isn't the right tool for designing and testing actions.
References:
* Salesforce Copilot Builder Overview:https://help.salesforce.com/s/articleView?id=sf.
einstein_copilot_builder.htm


NEW QUESTION # 108
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?

  • A. Einstein Reply Recommendations and Case Classification
  • B. Einstein Service Replies and Work Summaries
  • C. Einstein Reply Recommendations and Case Summaries

Answer: A

Explanation:
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.
References:
* 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)


NEW QUESTION # 109
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