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| Section | Weight | Objectives |
|---|---|---|
| Optimize AI-driven sales workflows and insights | 20-25% | - Configure Sales accelerator and work distribution - Configure Copilot for Sales - Set up conversational intelligence - Implement predictive scoring and relationship intelligence |
| Configure Dynamics 365 Sales core features for AI | 15-20% | - Design and configure sales data model - Configure security and access for AI features - Set up core sales entities and relationships - Integrate Microsoft Power Platform components |
| Develop deals by using intelligent opportunity research | 25-30% | - Configure forecasting and goal management - Use AI for opportunity research and insights - Deploy and configure Sales Close Agent - Optimize opportunity management workflows |
| Qualify and prioritize leads by using AI | 15-20% | - Configure lead qualification processes - Automate lead routing and prioritization - Implement Sales Qualification Agent - Fine-tune predictive lead scoring models |
| Extend and enhance sales solutions with AI | 10-15% | - Monitor and optimize AI performance - Deploy and manage AI agents - Implement collaboration features - Configure reporting and visualization |
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NEW QUESTION # 37
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 # 38
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 # 39
A company is using AI agents in Dynamics 365 Sales.
The company requires that the agent must do the following:
- Research incoming leads and generate initial outreach email.
- Autonomously contact leads, follow up, and evaluate qualification
during the process.
You need to identify which AI agent in Sales supports these requirements.
Which agent type should you use?
Answer: B
Explanation:
The correct agent type is Sales Qualification Agent: Research and engage. The requirement is specifically about inbound lead processing: researching incoming leads, generating outreach, autonomously contacting leads, following up, and evaluating qualification during the engagement process. Microsoft defines Sales Qualification Agent as the AI agent used to automate lead qualification in Dynamics 365 Sales, especially for high-volume inbound leads from sources such as websites, events, and webinars. In Research and engage mode, the agent researches the lead, evaluates fit using target customer profile and BANT criteria, sends personalized outreach emails, engages based on responses, sends follow-up emails, detects positive intent, and then hands promising leads to sellers.
Research-only mode is not enough because it generates a draft outreach email for seller review but does not send outreach emails or detect positive intent from responses. Microsoft's mode comparison explicitly shows that BANT checking, sending outreach, detecting positive intent, and follow-up emails are available in Research and engage mode, not Research-only mode. Sales Close Agent options are wrong because they apply to opportunity/deal execution, not initial lead qualification.
NEW QUESTION # 40
A sales team contacts customers to promote and sell products.
You need the sales team to place outbound calls directly from Dynamics 365 Sales records using Microsoft Teams.
You need to enable calling directly from records.
What should you configure?
Answer: C
Explanation:
The correct configuration is to enable the Microsoft Teams dialer. Microsoft's Dynamics 365 Sales documentation states that Microsoft Teams dialer brings Teams calling directly into Dynamics 365 Sales so sellers can make and receive calls without leaving the application. The documented setup path is to go to Sales Hub app settings, open Teams calls, and turn on Teams calls for the selected security roles and apps.
This matches the requirement precisely: the sales team must place outbound calls directly from Dynamics 365 Sales records using Microsoft Teams. Phone numbers and PSTN connectivity are prerequisites for Teams calling, but option A is not the Dynamics 365 Sales feature that enables record-level calling. The mobile app is irrelevant because the question asks for calling from Dynamics 365 Sales records, not mobile access. Teams meeting integration supports meetings and collaboration, but it does not enable click-to-call or Teams dialer calling from Sales records.
Therefore, the required feature is Microsoft Teams dialer.
NEW QUESTION # 41
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 # 42
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