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| Section | Weight | Objectives |
|---|---|---|
| Qualify and prioritize leads by using AI | 15-20% | - Implement Sales Qualification Agent - Fine-tune predictive lead scoring models - Automate lead routing and prioritization - Configure lead qualification processes |
| Optimize AI-driven sales workflows and insights | 20-25% | - Set up conversational intelligence - Configure Copilot for Sales - Implement predictive scoring and relationship intelligence - Configure Sales accelerator and work distribution |
| Configure Dynamics 365 Sales core features for AI | 15-20% | - Integrate Microsoft Power Platform components - Design and configure sales data model - Set up core sales entities and relationships - Configure security and access for AI features |
| Extend and enhance sales solutions with AI | 10-15% | - Configure reporting and visualization - Deploy and manage AI agents - Implement collaboration features - Monitor and optimize AI performance |
| Develop deals by using intelligent opportunity research | 25-30% | - Deploy and configure Sales Close Agent - Use AI for opportunity research and insights - Optimize opportunity management workflows - Configure forecasting and goal management |
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NEW QUESTION # 63
Hotspot Question
A company plans to implement AI capabilities in Dynamics 365 Sales to automate multiple seller workflow tasks.
The company needs to assign AI capabilities that provide the following:
- Must identify contextual insights about accounts before outreach.
- Must generate overviews of opportunity activities and emails.
- Must evaluate and qualify incoming leads automatically.
You need to match the appropriate AI capability to each seller workflow task.
Which configuration should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The correct capability for identifying contextual account insights before outreach is Sales Research Agent. This agent is designed to help sellers and sales leaders gather AI-generated research about customers, prospects, and sales targets, which directly supports pre-outreach preparation and account intelligence. It is not Conversation Intelligence, because Conversation Intelligence analyzes calls and seller-customer conversations after or during interactions, not account research before outreach.
For generating an opportunity overview, the correct capability is Copilot summarization. Copilot in Dynamics 365 Sales can generate quick summaries of opportunity and lead records, including relevant activity and communication context, so sellers can quickly understand the state of a deal without manually reviewing all historical interactions.
For automating lead processing, the correct capability is Sales Qualification Agent. This agent evaluates incoming leads against qualification criteria, researches lead context, determines fit, and can qualify or disqualify leads according to configured business rules. Predictive lead scoring prioritizes leads by likelihood to convert, but it does not perform autonomous lead qualification processing. Sales Close Agent is focused on opportunity/deal execution, not lead qualification.
NEW QUESTION # 64
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 # 65
You need to allow sellers to view leads disqualified by the Sales Qualification Agent in production.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
Answer: A,C
Explanation:
The required fix is about visibility and security , not agent operating mode. In the scenario, production has EnableRoleBasedSystemViews set to true, which restricts system views based on role configuration. Because the business requirement says all sellers should be able to access disqualified leads , the role-based system view setting must be updated so sellers can access the view that exposes leads disqualified by the Sales Qualification Agent.
The second required action is to change Lead table permissions. The customized Salesperson role currently grants sellers read access only to leads they own. That is too restrictive because leads disqualified by the Sales Qualification Agent may not be owned by each seller. To let all sellers view those records, sellers need organization-level Read permission on the Lead table. Option A is wrong because upgrading the agent to research and engage mode affects how the agent researches and interacts with leads; it does not solve seller access to disqualified records. Option C is also wrong because the look-back period controls which historical leads the agent evaluates, not who can view disqualified leads.
References/topics: Sales Qualification Agent; role-based system views; Dataverse security roles; Lead table read access; AI-driven lead qualification.
NEW QUESTION # 66
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.
NEW QUESTION # 67
A sales manager needs to set up goals in Dynamics 365 Sales for salespeople.
The measurement of goals must be based on the total deal amount upon closing an opportunity.
The fiscal year for the goals must be based on the calendar year.
You need to create the rollup query for the goal metrics.
Which options should you select? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Parameter
Option
Entity
Opportunity
Date field
Actual Close Date
Revenue field
Actual Revenue
The correct table is Opportunity because the goal measurement is based on deal amounts when opportunities are closed. In Dynamics 365 Sales goal metrics, rollup fields define which table and source attribute are used to calculate actual or in-progress goal values. Microsoft's goal metric documentation gives the direct example of using the Opportunity table with the opportunity actual value/source attribute to track actual money amounts from opportunities closed as Won .
The correct date field is Actual Close Date because the goal period must be determined by when the deal was actually closed, not when the opportunity was created. Microsoft's goal metric configuration guidance states that the Date Field determines the goal period that records roll up into, and gives Actual Close Date as the relevant example.
The correct revenue field is Actual Revenue because the requirement is based on the total deal amount upon closing the opportunity. Budget Amount and Total Amount do not represent the final closed deal value for goal actuals. Goal rollup fields calculate actual performance values for completed measurable results, which fits closed opportunity revenue.
References/topics: Dynamics 365 Sales goals; goal metrics; rollup fields; opportunity actual revenue; actual close date; sales performance tracking.
NEW QUESTION # 68
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