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| Section | Weight | Objectives |
|---|---|---|
| Develop deals using intelligent opportunity research | 25–30% | - Configure Sales Close Agent and interpret actions - Configure and use Sales Research Agent insights - Optimize opportunity management and pipeline views |
| Optimize AI-driven sales | 20–25% | - Configure predictive scoring and relationship intelligence - Set up conversational intelligence and forecasting - Prepare and deploy AI agents in Sales - Design AI-first sales strategy with Copilot and agents |
| Qualify and prioritize leads using AI | 15–20% | - Configure lead and opportunity experience - Fine-tune predictive scoring model - Configure Sales Qualification Agent and monitor its performance |
| Configure Dynamics 365 Sales core features for AI | 15–20% | - Configure timeline and data import/export - Configure mailboxes and business process flows - Evaluate prerequisites for deploying Sales - Examine Sales security model |
| Extend and enhance Sales | 10–15% | - Deploy and configure Sales mobile app and Teams calling - Create Power Platform components (Power Automate, Power Apps, Power BI) |
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NEW QUESTION # 78
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 # 79
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.
You are deploying AI agents for a company using Microsoft Dynamics 365 Sales.
The company wants to ensure that AI usage is tracked and billed monthly.
The company requires that AI billing uses pre-paid credits.
You need to configure the billing based on the requirements.
Solution: Create a billing policy for the Dynamics 365 Sales environment.
Does the solution meet the goal?
Answer: A
Explanation:
The solution does not meet the goal because a billing policy for the Dynamics 365 Sales environment is associated with the pay-as-you-go consumption model, not the prepaid-credit model required in the question. Microsoft separates Dynamics 365 Sales Copilot and agent billing into two models:
prepaid capacity and pay-as-you-go. Prepaid capacity uses Copilot Studio message pack subscriptions that are purchased in advance, while pay-as-you-go charges for the actual number of messages consumed by agents during the month.
For prepaid AI credits, the correct configuration is to purchase the Copilot message pack subscription and then assign that prepaid capacity to the required Power Platform/Dynamics 365 Sales environment. Microsoft's setup steps for prepaid capacity specifically state that admins must purchase Copilot message packs through the Microsoft 365 admin center or Partner Center and assign prepaid capacity to the Power Platform environment through the Power Platform admin center.
So the proposed solution is wrong for the stated requirement. It may support monthly tracked consumption under pay-as-you-go, but it does not satisfy the explicit requirement to use pre-paid credits.
NEW QUESTION # 80
Drag and Drop Question
A company uses the Sales Close Agent to assist sellers during the closing phase of opportunities.
The Sales Close Agent must meet the following requirements:
- Recommend targeted action for disengaged deals.
- Generate insights from CRM records, emails, meetings, and web
research into a unified deal view.
- Ensure customer interactions are compliant with company policies.
You need to identify the agent mode for each requirement.
Which agent mode should you recommend? To answer, move the appropriate requirements to the correct agent modes. You may use each agent mode 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:
The first two requirements belong to Research mode because they are insight-generation functions for opportunity management. Microsoft describes the opportunity-focused Sales agent as identifying risks such as disengaged stakeholders, slowing momentum, and competitive pressure, then recommending targeted actions to keep the deal moving forward. It also provides a comprehensive deal view by surfacing buyer needs, stakeholder roles, competitor mentions, and deal health in one unified place. This directly matches both "recommend targeted action for disengaged deals" and "generate insights from CRM records, emails, meetings, and web research into a unified deal view." The compliance requirement maps to Engage mode because compliance matters when the agent communicates externally with customers. Sales Close Agent Engage mode automates customer engagement through outreach and follow-up emails, and Microsoft states that admins configure an email delivery compliance profile so the agent's communications follow organizational policies and regulatory requirements. Research mode produces insights for sellers; it does not perform customer outreach. Therefore, use Research for opportunity intelligence and Engage for compliant customer interaction.
NEW QUESTION # 81
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 # 82
A company wants AI recommendations without replacing existing sales methodologies or approval processes. Which statement best reflects Dynamics 365 Sales AI?
Answer: B
Explanation:
Dynamics 365 Sales AI is designed to enhance existing sales methodologies by providing recommendations, predictions, and automation. Organizations continue using their established approval processes, governance, and CRM configurations while benefiting from AI-assisted productivity.
NEW QUESTION # 83
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