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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Qualify and prioritize leads using AI | 15–20% | - Configure Sales Qualification Agent and monitor its performance - Fine-tune predictive scoring model - Configure lead and opportunity experience |
| Topic 2: Configure Dynamics 365 Sales core features for AI | 15–20% | - Evaluate prerequisites for deploying Sales - Configure timeline and data import/export - Configure mailboxes and business process flows - Examine Sales security model |
| Topic 3: Develop deals using intelligent opportunity research | 25–30% | - Configure and use Sales Research Agent insights - Optimize opportunity management and pipeline views - Configure Sales Close Agent and interpret actions |
| Topic 4: Optimize AI-driven sales | 20–25% | - Design AI-first sales strategy with Copilot and agents - Prepare and deploy AI agents in Sales - Set up conversational intelligence and forecasting - Configure predictive scoring and relationship intelligence |
| Topic 5: 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 |
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NEW QUESTION # 35
You are creating a pricing list in Dynamics 365 Sales. All prices must end in $.98.
You need to select the function that establishes this pricing requirement.
What should you use?
Answer: A
Explanation:
The correct answer is Rounding Amount. In Dynamics 365 Sales price list item configuration, rounding is used when calculated prices must follow a specific price-ending convention, such as ending in .98 or .99. Microsoft's pricing guidance explains that price list items can use rounding behavior so calculated product prices can be rounded and made to end in a specified amount, such as 99 cents. The value that defines the exact ending amount is the Rounding Amount.
Therefore, to make all calculated prices end in $.98, the administrator would configure the rounding amount as 0.98.
Rounding Policy is not precise enough by itself. It controls the direction of rounding, such as rounding up, down, or to the nearest value, but it does not define the exact cents-ending requirement. Pricing Method determines how the price is calculated, such as a currency amount, percentage of list price, markup, or margin. Percentage is used when a percentage-based pricing method is selected, but it does not force prices to end in $.98. The requirement is explicitly about the final rounded price ending, so Rounding Amount is the correct function.
NEW QUESTION # 36
You use price lists in Dynamics 365 Sales. Some price lists have expired.
Users need to be able to continue to manage their opportunities.
Which option is possible?
Answer: D
NEW QUESTION # 37
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 # 38
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: Use Research mode and allow sellers to review insights manually.
Does the solution meet the goal?
Answer: B
Explanation:
Yes, the solution meets the goal. The requirement has two parts: sales managers need deal insights , and the system must not automatically perform outreach to buyers. Sales Close Agent in Research mode is the correct fit because it researches opportunities, calculates importance and risk, generates summaries, and provides actionable recommendations for sellers to review manually. Microsoft states that the opportunity research experience shows a summary and a See full research page with complete opportunity insights and recommendations.
Research mode is intentionally different from Engage mode. Engage mode is the autonomous customer- interaction mode; Microsoft describes Sales Close Agent Engage as managing customer interactions and driving sales for high-velocity deals. By contrast, Research mode focuses on research, opportunity insights, risks, and seller guidance. Microsoft's configuration guidance for Sales Close Agent Research describes selecting opportunities to research, configuring refresh frequency, and providing company context so the agent can curate research insights. Therefore, using Research mode while requiring sellers to manually review the insights satisfies both requirements: the organization receives AI-generated deal intelligence, but buyer outreach remains under human seller control.
References/topics: Sales Close Agent Research mode; opportunity research insights; manual seller review; Engage mode versus Research mode; AI-supported opportunity management.
NEW QUESTION # 39
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: D
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.
NEW QUESTION # 40
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