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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Extend and enhance Sales | 10–15% | - Create Power Platform components (Power Automate, Power Apps, Power BI) - Deploy and configure Sales mobile app and Teams calling |
| Topic 2: Configure Dynamics 365 Sales core features for AI | 15–20% | - Evaluate prerequisites for deploying Sales - Configure timeline and data import/export - Examine Sales security model - Configure mailboxes and business process flows |
| Topic 3: Develop deals using intelligent opportunity research | 25–30% | - Optimize opportunity management and pipeline views - Configure and use Sales Research Agent insights - Configure Sales Close Agent and interpret actions |
| Topic 4: Qualify and prioritize leads using AI | 15–20% | - Configure Sales Qualification Agent and monitor its performance - Configure lead and opportunity experience - Fine-tune predictive scoring model |
| Topic 5: Optimize AI-driven sales | 20–25% | - Set up conversational intelligence and forecasting - Configure predictive scoring and relationship intelligence - Design AI-first sales strategy with Copilot and agents - Prepare and deploy AI agents in Sales |
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NEW QUESTION # 51
A seller asks Copilot to prepare for an upcoming customer meeting. The customer has multiple open opportunities, recent emails, and support cases. What should Copilot primarily generate?
Answer: B
Explanation:
Copilot can generate meeting preparation summaries by combining CRM records, customer communications, opportunity status, and related activities. The summary provides sellers with relevant business context before customer meetings, improving readiness while reducing manual research.
NEW QUESTION # 52
A company implements Dynamics 365 Sales.
The company has the following requirements:
- Employees must have quarterly goals. The goals must calculate all
deals won by quarter for each goal.
- Managers must be able to look at the goals and calculations at any
time.
The solution must use goal features WITHOUT customization.
You need to create the calculation.
What should you configure?
Answer: B
Explanation:
The correct answer is Goal metric. In Dynamics 365 Sales, the goal metric defines how goal performance is calculated. Microsoft explains that each goal uses a goal metric to determine how the goal is tracked, and goal metrics can track actual, in-progress, and custom values through rollup fields. For won opportunity revenue, the metric can use the Opportunity table as the source and roll up the actual value for opportunities that are closed as won.
The quarterly requirement is handled by the goal's time period. The goal metric specifies the calculation logic, including the source table, source attribute, date attribute, and source status such as Won. Microsoft's goal metric documentation states that the date attribute is validated against the goal time period, so records participate in the rollup only when their date falls between the goal start and end dates. A rollup query is not the best answer because it only applies additional filtering criteria to an existing goal metric; it does not create the core calculation.
NEW QUESTION # 53
You need to configure the new lead qualification experience in Dynamics 365 Sales for field sellers.
What should you configure?
Answer: C
Explanation:
The correct configuration is to set related record creation to Seller. The case study states that sales leadership requires flexibility in how leads are converted: inside sales need automatic opportunity creation, but field sellers need the option to manually decide whether an opportunity should be created when a lead is qualified.
In the new lead qualification experience, Dynamics 365 Sales lets administrators control whether account, contact, and opportunity records are created automatically during lead qualification or whether sellers are prompted to choose which related records to create. Microsoft's lead qualification guidance confirms that when automatic creation is not enabled, sellers are prompted to select which records should be created during qualification.
Option B and option E are wrong for field sellers because automatic creation would remove the manual decision point required by the case study. Option C is relevant to guiding sellers through sales stages, but the existing Lead to Opportunity Business Process Flow does not control whether related records are automatically created when a lead is qualified. Option D is unrelated because Copilot summaries help sellers review record information; they do not configure lead conversion behavior. Therefore, the required configuration for field sellers is Seller-controlled related record creation.
References/topics: Lead qualification experience; lead-to-opportunity conversion; related account, contact, and opportunity creation; Dynamics 365 Sales lead management.
NEW QUESTION # 54
A sales team uses Dynamics 365 Sales to manage leads and opportunities.
Sales managers must be able to ensure that every qualified lead results in a follow-up task for the opportunity owner.
You need to create an automated solution by using Power Automate.
Which type of trigger should you use to start the flow?
Answer: A
Explanation:
The correct trigger type is Automated . The requirement is event-driven: when a lead is qualified and an opportunity is created or updated, the system must automatically create a follow-up task for the opportunity owner. In Power Automate, this is implemented as an automated cloud flow that starts when a Dataverse event occurs, such as when a row is added, modified, or deleted. Microsoft's Dataverse trigger documentation states that the When a row is added, modified or deleted trigger runs a flow whenever a selected Dataverse table row is created or changed.
A scheduled trigger is wrong because the requirement is not time-based. Running the process hourly or daily would delay task creation and could miss the intended immediate follow-up behavior. An instant trigger is also wrong because it requires a user to manually start the flow. Microsoft describes instant cloud flows as manually triggered flows, while automated flows run after an event triggers them. For this case, the flow should listen for the qualifying lead or opportunity event in Dataverse, then create the follow-up task and assign it to the opportunity owner.
References/topics: Power Automate automated cloud flows; Dataverse row triggers; lead qualification; opportunity follow-up task automation; Dynamics 365 Sales extensibility.
NEW QUESTION # 55
Case Study 2 - Contoso Ltd
Background
Contoso Ltd. is a global technology distributor headquartered in Redmond, Washington. The company sells networking equipment, cloud infrastructure, and managed services to enterprise customers across North America and Europe.
Contoso Ltd. currently manages its sales operations by using Microsoft Dynamics 365 Sales and plans to enable Sales Insights in the future.
The leadership team wants to modernize the sales organization by introducing capabilities that help sellers prioritize leads, analyze opportunities, and accelerate deal closure.
The company has approximately 150 field sellers, 40 insider sellers, 20 sales managers, and a central IT team responsible for configuring the sales platform. Contoso Ltd.'s executive leadership has defined the following goals for the new sales platform implementation:
Improve seller productivity by reducing manual research and data entry.
Use Al insights to prioritize leads and opportunities.
Provide automated recommendations to sales representatives throughout the deal lifecycle.
Improve collaboration between sellers and sales managers.
Current Environment:
Sales platform
Contoso Ltd. uses Microsoft Dynamics 365 Sales integrated with Microsoft 365 services.
The following components are currently deployed:
Data and lead management
Leads are important for driving new business at Contoso Ltd. They are generated from multiple sources including:
- Marketing automation campaigns
- Website registrations
- Partner referrals
- Trade show contact imports
Marketing teams import lead lists weekly into Dynamics 365 Sales by using spreadsheet imports.
Sellers currently evaluate leads manually.
Sales managers report that this process results in inconsistent prioritization across regions.
Opportunity management
Opportunities are tracked in Dynamics 365 Sales through a defined qualification-to-opportunity lifecycle to ensure accurate reporting.
Sales leadership has requested the Contoso Ltd. IT team to evaluate the following capabilities:
- AI-generated summaries of opportunity records.
- AI-driven research for customer organizations.
- Automated recommendations for closing deals.
Business Requirement:
Contoso Ltd.'s executives have defined the following business requirements:
Lead management
Inside sellers must use a seller engagement workspace that prioritizes leads automatically based on predicted likelihood to convert.
All sellers are guided through a consistent set of qualification steps aligned to Contoso Ltd.'s sales strategy.
Leads cannot be advanced to the development stage until a decision maker has been confirmed.
Sales leadership requires flexibility in how leads are converted. Inside sales need automatic opportunity creation. Field sellers need the option to manually decide whether an opportunity should be created when a lead is qualified.
Lead scoring must be implemented to help sellers identify high potential leads automatically.
Lead scoring must continuously improve based on historical sales outcomes.
Opportunity development
The opportunity flow must be improved by using Al-driven research and automated insights.
Field sellers must be able to access contextual research about customers and competitors while working on opportunities.
Opportunity records must display Al-generated summaries to reduce the time required to review historical activities.
Field sellers must use the Opportunity pipeline view to visualize, prioritize, and manage opportunities.
All opportunity revenue must be calculated using opportunity line items based on selected Contoso Ltd.'s products and standard pricing.
Sales managers must receive an external quarterly competitive intelligence brief to help with their research. This should be delivered as a PDF document.
Sales performance
Sales managers require improved pipeline and revenue forecasting capabilities. The managers need to report on their business performance and use insights, visuals, and recommended next actions.
The new solution must provide the following:
- Allow sales managers to configure forecasts for opportunity pipelines.
- Notify the seller's manager when a draft quote is created and requires approval.
- Allow leadership to track performance against revenue goals.
- Ask questions about Dynamics 365 Sales data to support executive analysis and decision making.
- Support data definitions used at Contoso Ltd. when reporting.
Technical Requirement:
Contoso Ltd.'s IT department defines the following priorities for the sales platform.
AI capabilities
The platform must support the following Al features:
- Lead scoring to guide sellers to priority items.
- Opportunity research insights to prepare deal analysis.
- Copilot-generated summaries of sales records to help with decision making.
- AI-powered research and analytics to aid leadership reporting.
- When performing sales research, sales managers must be able to save their favorite prompts.
Automation
Automation must be implemented to guide sellers through recommended next steps during the sales cycle.
Any approvals must use the Power Automate Approvals connector.
Field sellers use the existing Lead to Opportunity Business Process Flow to manage their leads.
A Power Automate desktop flow is used to process orders into a partner ordering application that completes fulfillment.
Collaboration
All sellers must be able to collaborate by using Teams and store related sales documents in SharePoint.
AI-driven insights
The company is deploying the Sales accelerator to guide seller activities.
The Sales Research Agent
Sales managers will use the Sales Research Agent to gather intelligence about customer organizations.
The sales managers have the following requirements:
- Must be able to reuse visualizations after they are created; they don't want to recreate them.
- Must have a consistent method to quickly return to a blueprint that they frequently use.
- Must be able to retain a library of questions to receive consistent responses based on definitions approved by the company.
- Should have Bing search enabled on the environment for generative Al feature settings.
Platform extensions
The IT department plan to extend the platform by doing the following:
- Create Power Automate flows to automate seller tasks.
- Embed Power Apps components inside model-driven forms.
- Embed Power BI reports for sales analytics.
Testing
The IT department is testing predictive lead scoring with a small group of sellers.
The IT department edits the existing lead scoring model by adding new fields.
Issues:
Users have reported the following issues:
- Field sellers spend a significant amount of time researching customers before engaging with prospects.
- Sales managers cannot easily identify the most promising opportunities across regions.
- Lead prioritization varies significantly between sales teams.
- Testers report they cannot access the field changes in the lead score.
- A sales manager generated a blueprint but forgot the competitive intelligence brief.
Hotspot Question
You need to configure AI capabilities that prioritize leads and improve scoring accuracy in Dynamics 365 Sales.
How should each requirement be configured? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation:
The correct capability for automatically prioritizing leads based on conversion probability is Predictive lead scoring. Dynamics 365 Sales predictive lead scoring assigns scores to leads so sellers can prioritize the leads most likely to qualify or convert. Microsoft's Sales documentation states that predictive lead scoring helps sales teams prioritize leads based on scores and improve lead qualification outcomes. This directly matches Contoso's requirement to guide sellers toward high- potential leads and reduce inconsistent manual prioritization across regions.
To meet the requirement that lead scoring must continuously improve based on historical sales outcomes, configure the model to automatically retrain. Microsoft's predictive lead scoring guidance explains that retraining uses the latest leads in the organization to improve model accuracy, and automatic retraining allows the application to retrain the model every 15 days. This is the correct option because Contoso wants the scoring model to improve continuously as more closed lead outcome data becomes available.
"Lead scoring model" is too generic; the AI capability required is specifically predictive lead scoring. "Relationship intelligence" supports relationship analytics and engagement insights, but it does not score leads by conversion probability. "Configure forecast" applies to pipeline forecasting, not lead scoring accuracy.
NEW QUESTION # 56
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