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| Section | Weight | Objectives |
|---|---|---|
| Optimize AI-driven sales | 20–25% | - Configure predictive scoring and relationship intelligence - Design AI-first sales strategy with Copilot and agents - Prepare and deploy AI agents in Sales - Set up conversational intelligence and forecasting |
| 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 |
| Develop deals using intelligent opportunity research | 25–30% | - Optimize opportunity management and pipeline views - Configure and use Sales Research Agent insights - Configure Sales Close Agent and interpret actions |
| Qualify and prioritize leads using AI | 15–20% | - Configure Sales Qualification Agent and monitor its performance - Configure lead and opportunity experience - Fine-tune predictive scoring model |
| 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 # 82
A company uses Dynamics 365 Sales to manage enterprise opportunities. The sales team enables the Sales Research Agent to generate research summaries for each opportunity.
Sales managers must determine whether opportunities have strong external indicators that support deal progression.
You need to analyze insights from the research canvas for evidence that a deal environment is favorable.
Which two research canvas insights should you provide to the sales managers? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
The correct insights are recent public developments and strategic landscape analysis relative to the seller's value proposition. The question is asking for external indicators that show whether the account's deal environment is favorable. Sales Research Agent is designed to analyze business questions using sales and business data, generate a blueprint with analysis, recommendations, charts, and graphs, and allow users to add external data sources such as PDFs, Excel, or CSV files to augment research. Microsoft describes the blueprint as a research output containing findings, visualizations, and recommendations that can support evidence-based sales decisions.
Option B is correct because recent public developments can reveal external buying triggers, market pressure, expansion activity, regulatory change, funding, partnerships, or competitive movement that may support deal progression. Option D is correct because strategic landscape analysis connects those external conditions to the seller's value proposition, which is exactly what managers need to judge deal favorability.
NEW QUESTION # 83
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: C
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 # 84
Your company is preparing sellers for complex enterprise opportunities.
The company wants sellers to gather relevant insights before initial account engagement.
You need to determine when using the Sales Research Agent is appropriate.
In which two scenarios are you able to use the Sales Research Agent? Each correct answer is a complete solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
The correct scenarios are B and C . Sales Research Agent is designed for research and analysis, not autonomous record updates or email engagement. Microsoft describes the agent as an AI-powered research canvas that lets users solve complex business questions through natural language, generate research blueprints, review sales-data insights, and ask follow-up questions to refine the analysis. It can use Dynamics
365 Sales data, uploaded offline files such as CSV, Excel, or PDF, and connected data sources to support pipeline exploration and sales operations analysis.
Option B is correct because Microsoft states that Sales Research Agent may use Bing Search only when the Bing search consent setting is enabled. When Bing search is disabled, the agent operates only on internal data sources that the user already has permission to access. Option C is also correct because the agent generates a research blueprint with visualizations and a text overview, and users can continue iterating by asking follow- up questions or changing visualizations on the canvas. Option A is wrong because Sales Research Agent is analytical; it does not update opportunities with risk or importance values. Option D is wrong because automatic email engagement is the domain of sales/qualification engagement agents, not Sales Research Agent.
References/topics: Sales Research Agent; research canvas; AI-generated blueprints; Bing search consent; internal sales data analysis; intelligent opportunity research.
NEW QUESTION # 85
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:
Requirement
Agent mode
Recommend action for disengaged deals
Research
Generate insights from records and research into a unified deal view
Research
Ensure customer interactions are compliant
Engage
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.
References/topics: Sales Close Agent; Sales Opportunity Agent Research mode; Sales Close Agent Engage mode; opportunity risk insights; compliance profile for agent email communications.
NEW QUESTION # 86
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 # 87
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