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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop deals by using intelligent opportunity research | 25-30% | - Use AI for opportunity research and insights - Configure forecasting and goal management - Optimize opportunity management workflows - Deploy and configure Sales Close Agent |
| Topic 2: Qualify and prioritize leads by using AI | 15-20% | - Implement Sales Qualification Agent - Configure lead qualification processes - Fine-tune predictive lead scoring models - Automate lead routing and prioritization |
| Topic 3: Optimize AI-driven sales workflows and insights | 20-25% | - Configure Copilot for Sales - Set up conversational intelligence - Implement predictive scoring and relationship intelligence - Configure Sales accelerator and work distribution |
| Topic 4: Extend and enhance sales solutions with AI | 10-15% | - Implement collaboration features - Configure reporting and visualization - Deploy and manage AI agents - Monitor and optimize AI performance |
| Topic 5: Configure Dynamics 365 Sales core features for AI | 15-20% | - Set up core sales entities and relationships - Design and configure sales data model - Integrate Microsoft Power Platform components - Configure security and access for AI features |
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NEW QUESTION # 72
A seller asks Copilot to identify important customer concerns discussed across multiple emails before preparing a proposal. Which capability should be used?
Answer: A
Explanation:
Conversation summarization analyzes multiple email exchanges to identify recurring concerns, commitments, questions, and discussion themes. Sellers receive a concise overview that helps them prepare proposals aligned with customer priorities and expectations.
NEW QUESTION # 73
A company plans to implement Dynamics 365 Sales and wants to design a Dataverse data model that supports AI-driven insights across the sales lifecycle.
The company must be able to track the progression of a deal from initial prospect identification through to finalized billing.
The data model must support the following requirements:
- Prospects must be captured before they become qualified sales deals.
- Qualified deals must support forecasting and pipeline analysis.
- Sales teams must be able to generate pricing proposals for customers.
- Accepted proposals must transition into fulfillment records and then
final billing records.
You need to design the Dataverse table model that supports the required sales lifecycle.
Which table relationship should you implement?
Answer: E
Explanation:
The correct sales lifecycle is Lead -> Opportunity -> Quote -> Order -> Invoice. In Dynamics 365 Sales, a lead captures an initial prospect before the person or organization is qualified.
Microsoft's sales process guidance explains that sellers generally work with leads during the qualifying stage, and the goal is to qualify and advance the lead to the next stage of the sales process. Once qualified, the deal becomes an opportunity, which is the record used for pipeline tracking, revenue estimation, sales stages, probability, and forecasting analysis. Microsoft's prospect-to-quote guidance states that Dynamics 365 Sales supports capturing, managing, scoring, and converting leads into opportunities when qualification criteria are met.
Quotes are then created from opportunities to present pricing proposals to customers. Microsoft states that quotes created from opportunities are prefilled with opportunity details and products.
Once the proposal is accepted, the quote can be converted into a sales order for fulfillment and then into an invoice for billing; Microsoft's quote/order/invoice process sample explicitly demonstrates converting an opportunity to a quote, a quote to a sales order, and a sales order to an invoice. Therefore, option B is the only sequence that correctly supports the full sales lifecycle.
NEW QUESTION # 74
You need to configure AI-powered research capabilities for the sales team.
What should you configure? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all.
Answer:
Explanation:
Explanation:
Requirement
Configuration
Blueprints
Name the blueprint workspace and pin the workspace.
Questions
Create a business function with seeded prompts.
For Blueprints, the correct configuration is to name the blueprint workspace and pin the workspace. The requirement is not asking to regenerate analysis; it asks for a reliable way to return to frequently used research output. In Sales Research Agent, a generated blueprint exists inside a workspace, and Microsoft states that the workspace displays the workspace name, can be renamed, and can be switched from the workspace menu.
That makes naming and pinning the workspace the correct operational pattern for reusable research access.
For Questions, the correct configuration is to create a business function with seeded prompts. Sales Research Agent business functions are designed to tailor research to a specific use case, and administrators can add starter prompts. Microsoft explains that starter prompts appear on the Sales Research Agent home page for quick access and that the full prompt is sent to the agent when selected. This directly satisfies the requirement to retain a reusable library of approved questions.
Do not select regenerate the blueprint because regeneration refreshes or recreates analysis, but it does not create a persistent shortcut to frequently used research. Do not select custom table or manual prompt questions in Sales Copilot because the native Sales Research Agent feature already supports reusable business- function prompts.
References/topics: Sales Research Agent; research blueprints; workspace management; business functions; seeded/starter prompts; intelligent opportunity research.
NEW QUESTION # 75
You are implementing a sales automation solution for a company.
The sales team wants to automate actions when new leads are created or when opportunities reach specific milestones. The company plans to use Power Automate to automate these actions.
The automation must meet the following requirements:
. Automatically notify a manager when a high-value opportunity is created.
. Validate the products with an external ERP system every Sunday.
. Display a guided lead qualification interface on the lead form.
. Update an external ERP system when an opportunity is won.
You need to identify which automation type to use for each requirement.
Which automation type should you use? To answer, move the appropriate automation types to the correct requirements. You may use each automation type once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Requirement
Automation type
Notify a manager when a high-value opportunity is created
Power Automate automated cloud flow
Validate the products with an external ERP system every Sunday
Power Automate scheduled cloud flow
Display a guided lead qualification interface on the lead form
Business process flow
Update an external ERP system when an opportunity is won
Power Automate automated cloud flow
A Power Automate automated cloud flow is the correct automation type when work must run automatically after a business event occurs. Microsoft describes cloud flows as flows that can perform actions automatically after an event triggers them, such as sending a notification after a triggering event occurs. Therefore, notifying a manager when a high-value opportunity is created and updating an external ERP system when an opportunity is won are both event-driven scenarios, so they should use automated cloud flows with Dataverse triggers.
A Power Automate scheduled cloud flow is correct for validating products with an external ERP system every Sunday. Microsoft states that a scheduled cloud flow runs at a specific time or recurring schedule, such as daily or weekly, and uses a recurrence trigger. That directly matches the weekly Sunday validation requirement.
A Business process flow is correct for displaying a guided lead qualification interface on the lead form.
Business process flows provide a streamlined user experience that guides users through defined processes, and Dynamics 365 Sales documentation explains that stages and steps display in a control at the top of a form.
Instant cloud flow is not used because none of the requirements ask for a manually triggered user action.
References/topics: Power Automate automated cloud flows; scheduled cloud flows; Dataverse triggers; Business process flows; Dynamics 365 Sales automation and extensibility.
NEW QUESTION # 76
A company is using Dynamics 365 Sales.
The company is NOT using predictive lead scoring. The company has historical sales records for the last three years.
You need to configure a predictive lead scoring model.
What is the minimum number of records required?
Answer: A
Explanation:
The minimum dataset for a predictive lead scoring model is 40 qualified leads and 40 disqualified leads .
Microsoft's Dynamics 365 Sales documentation states that an organization must have created and closed at least 40 qualified and 40 disqualified leads within the selected training period to train the model. The broader lead and opportunity scoring documentation confirms the same threshold and distinguishes lead scoring from opportunity scoring: lead scoring requires qualified and disqualified leads, while opportunity scoring requires won and lost opportunities.
This distinction is critical. Predictive lead scoring predicts the likelihood that a lead will qualify or convert based on historical lead outcomes, so the model needs examples of both successful and unsuccessful lead qualification results. Won and lost opportunities are not the correct training records for lead scoring; they apply to predictive opportunity scoring. The question also states that the company has historical sales records for three years, but the model requirement is based on the minimum qualifying lead dataset, not merely the total age of available data. Therefore, the required minimum is 40 qualified leads and 40 disqualified leads .
References/topics: Predictive lead scoring; lead scoring model prerequisites; qualified leads; disqualified leads; AI-driven lead prioritization.
NEW QUESTION # 77
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