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| Section | Weight | Objectives |
|---|---|---|
| Develop deals using intelligent opportunity research | 25–30% | - Optimize opportunity management and pipeline views - Configure Sales Close Agent and interpret actions - Configure and use Sales Research Agent insights |
| Optimize AI-driven sales | 20–25% | - Configure predictive scoring and relationship intelligence - Prepare and deploy AI agents in Sales - Design AI-first sales strategy with Copilot and agents - Set up conversational intelligence and forecasting |
| Qualify and prioritize leads using AI | 15–20% | - Configure lead and opportunity experience - Configure Sales Qualification Agent and monitor its performance - Fine-tune predictive scoring 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) |
| Configure Dynamics 365 Sales core features for AI | 15–20% | - Examine Sales security model - Configure mailboxes and business process flows - Configure timeline and data import/export - Evaluate prerequisites for deploying Sales |
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NEW QUESTION # 45
A seller receives dozens of customer emails daily. The organization wants AI to summarize long conversations and highlight important commitments before meetings. Which Copilot capability provides the greatest benefit?
Answer: B
Explanation:
Copilot email summarization analyzes lengthy conversations and produces concise summaries highlighting customer requests, commitments, and recent interactions. This reduces preparation time before meetings and helps sellers quickly understand ongoing discussions without reading every individual message.
NEW QUESTION # 46
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: B,C
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.
NEW QUESTION # 47
You are responsible for improving lead prioritization in Dynamics 365 Sales.
Sales managers report that predictive scores do not match current conversion trends.
You need to edit the predictive lead scoring model to improve accuracy based on recent lead data.
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 sequence starts by opening and configuring the predictive scoring settings for lead scoring. The administrator must access the predictive lead scoring configuration page before changing the model.
Microsoft's predictive scoring configuration guidance states that the Predictive lead scoring page is where administrators configure model settings, including model criteria and field behavior.
Next, the administrator should edit model attributes . This is the actual model-tuning step. Microsoft states that Edit model is used to update or add fields that affect the prediction accuracy score, especially when the organization wants the model to consider different fields or a unique business process.
After modifying the attributes, the model must be retrained . Retraining is required when prediction accuracy does not meet expectations or when recent data should be incorporated. Microsoft explains that retraining uses the latest leads in the organization so the model can provide more accurate scores.
Finally, the administrator must verify predictive score accuracy by reviewing the model accuracy and performance. Exporting all lead records is unnecessary, and editing health score grading applies to opportunity health scoring, not predictive lead scoring.
References/topics: Predictive lead scoring; model attributes; model retraining; scoring accuracy; lead prioritization in Dynamics 365 Sales.
NEW QUESTION # 48
A company wants AI recommendations without replacing existing sales methodologies or approval processes. Which statement best reflects Dynamics 365 Sales AI?
Answer: D
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 # 49
You are configuring Copilot capabilities in Dynamics 365 Sales for a company.
After enabling Copilot, sellers report that the summary insight banner on Opportunities, Leads, and Accounts is missing key business context and history.
You need to ensure that the missing information is displayed.
Which action should you perform?
Answer: D
Explanation:
The correct action is Configure table auditing . Copilot summaries and recent-change context for Opportunities, Leads, and Accounts depend on audit history. Microsoft's Dynamics 365 Sales Copilot setup guidance states that when Copilot is enabled, administrators can turn on audit history for the Lead, Opportunity, and Account tables, and Copilot needs audit history to display recent changes for those records.
This issue is not solved by predictive scoring or opportunity pipeline settings. Predictive scoring ranks leads or opportunities based on likelihood, but it does not provide historical summary context. The opportunity pipeline view controls how opportunities are displayed and managed in the pipeline, not what Copilot can summarize. AI insight cards are separate guided insight notifications and are not the underlying data-history source for the missing Copilot summary banner context. Microsoft also documents that Copilot's recent changes list is generated from audit history, and if auditing is turned off, the recent changes configuration is unavailable until auditing is enabled. Therefore, table auditing is the required configuration to make key history available for Copilot-generated summaries and recent-change insights.
References/topics: Copilot in Dynamics 365 Sales; record summaries; recent changes; Dataverse table auditing; Lead, Opportunity, and Account tables.
NEW QUESTION # 50
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