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| Section | Weight | Objectives |
|---|---|---|
| Configure Dynamics 365 Sales core features for AI | 15–20% | - Data and process setup for AI features - Sales environment configuration |
| Develop deals using intelligent opportunity research | 25–30% | - AI-assisted deal progression strategies - Opportunity insights and forecasting |
| Extend and enhance Sales | 10–15% | - Extending Dynamics 365 Sales with AI capabilities - Integration with Microsoft Copilot and Power Platform |
| Qualify and prioritize leads using AI | 15–20% | - AI-driven lead prioritization workflows - Lead scoring and qualification models |
| Optimize AI-driven sales | 20–25% | - Copilot and AI assistant capabilities in Sales - Sales productivity and automation enhancement |
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NEW QUESTION # 86
You need to automate the quote approval process.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
* Create a Power Automate cloud flow.
* Add a Dataverse trigger.
* Define an approval step.
* Test and activate the flow.
The correct automation pattern is an automated Power Automate cloud flow triggered by a Dataverse event.
The case study states that the process must notify the seller's manager when a draft quote is created and requires approval, and that approvals must use the Power Automate Approvals connector. Therefore, the flow should first be created as a cloud flow, then started by a Dataverse trigger such as when a row is added, modified, or deleted on the Quote table, filtered for the draft quote condition. Microsoft's Dataverse trigger guidance confirms that this trigger runs when a selected Dataverse table row is created, modified, or deleted.
After the trigger is defined, the flow must include an approval step using Power Automate approvals.
Microsoft's approval workflow guidance states that Power Automate can manage approvals across services including Dynamics 365 and Dataverse-based processes. The final action is to test and activate the flow so the quote approval automation is available to users. Do not use a scheduled trigger because the requirement is event-driven, not time-based. Do not connect to the existing desktop flow because that desktop flow processes partner orders for fulfillment, not draft quote approvals. A Teams step is optional collaboration, not the required approval mechanism.
References/topics: Power Automate cloud flows; Dataverse triggers; Approvals connector; Dynamics 365 Sales quote approval automation; sales platform extension.
NEW QUESTION # 87
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A company is evaluating AI agent capabilities for opportunity management.
Sales managers require insights about deals. You must ensure that the system does not perform automatic outreach to buyers.
You need to determine whether proposed solutions meet the requirements.
Solution: Configure the Sales Close Agent in Research mode.
Does the solution meet the goal?
Answer: B
Explanation:
Yes, the solution meets the goal. The requirement is very specific: sales managers need deal insights , but the organization must avoid automatic outreach to buyers . Sales Close Agent in Research mode is the correct configuration because it focuses on researching opportunities, analyzing deal context, identifying risks and signals, and providing recommendations to sellers without autonomously engaging customers.
Research mode is intended to help sellers understand an opportunity more quickly by surfacing insights such as deal health, signals, risks, and suggested next actions. It supports opportunity management by giving the team intelligence that can help progress deals, while leaving communication decisions in the hands of the seller. That directly aligns with the stated requirement for insights about deals.
The critical distinction is that Engage mode is the mode that performs automated outreach and customer interaction. Since the company explicitly does not want automatic outreach to buyers, Engage mode would violate the requirement. By configuring the Sales Close Agent in Research mode , the company gets AI- assisted opportunity analysis without autonomous communications.
References/topics: Sales Close Agent; Research mode; opportunity insights; deal analysis; recommended next actions; distinction between Research mode and Engage mode.
NEW QUESTION # 88
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-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:
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.
NEW QUESTION # 89
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.
Drag and Drop Question
You need to automate the quote approval process.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
The correct automation pattern is an automated Power Automate cloud flow triggered by a Dataverse event. The case study states that the process must notify the seller's manager when a draft quote is created and requires approval, and that approvals must use the Power Automate Approvals connector. Therefore, the flow should first be created as a cloud flow, then started by a Dataverse trigger such as when a row is added, modified, or deleted on the Quote table, filtered for the draft quote condition. Microsoft's Dataverse trigger guidance confirms that this trigger runs when a selected Dataverse table row is created, modified, or deleted.
After the trigger is defined, the flow must include an approval step using Power Automate approvals. Microsoft's approval workflow guidance states that Power Automate can manage approvals across services including Dynamics 365 and Dataverse-based processes. The final action is to test and activate the flow so the quote approval automation is available to users. Do not use a scheduled trigger because the requirement is event-driven, not time-based. Do not connect to the existing desktop flow because that desktop flow processes partner orders for fulfillment, not draft quote approvals. A Teams step is optional collaboration, not the required approval mechanism.
NEW QUESTION # 90
A seller is reviewing an opportunity in Dynamics 365 Sales. The Sales Close Agent in Research mode generates a summary.
The seller must decide how to proceed with the opportunity. The seller plans to use the research insights to move the deal forward.
You need to identify the information that the agent provides.
Which agent-provided insights should you share with the seller?
Answer: A
Explanation:
The correct insight to share is Recommended actions . Sales Close Agent in Research mode is opportunity- focused: it helps sellers understand the state of a deal, identify risks, and decide what to do next. Microsoft explains that the opportunity agent provides critical insights and recommendations so sellers can ramp up on opportunities, engage the right stakeholders, and mitigate risks effectively. The Responsible AI FAQ also describes the agent as identifying deal risks early and providing recommended mitigation strategies based on historical data and communication analysis.
The question specifically says the seller must decide how to proceed and wants to move the deal forward.
That points directly to recommended actions, not static context. Financial health may be part of a broader opportunity view, but it is not the best answer for next-step guidance. Budget, Authority, Need, and Timeline is BANT qualification and belongs to lead qualification scenarios, especially Sales Qualification Agent, not opportunity research. Blueprints are generated by the Sales Research Agent on a research canvas for analytics-style exploration, not by the Sales Close Agent opportunity summary. Therefore, the correct insight category is Recommended actions .
References/topics: Sales Close Agent Research mode; opportunity recommendations; deal risk mitigation; Sales Opportunity Agent insights; opportunity progression.
NEW QUESTION # 91
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