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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Optimize AI-driven sales | 20–25% | - Configure predictive scoring and relationship intelligence - Set up conversational intelligence and forecasting - Design AI-first sales strategy with Copilot and agents - Prepare and deploy AI agents in Sales |
| Topic 2: 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 |
| Topic 3: Configure Dynamics 365 Sales core features for AI | 15–20% | - Evaluate prerequisites for deploying Sales - Examine Sales security model - Configure mailboxes and business process flows - Configure timeline and data import/export |
| Topic 4: Qualify and prioritize leads using AI | 15–20% | - Configure lead and opportunity experience - Fine-tune predictive scoring model - Configure Sales Qualification Agent and monitor its performance |
| Topic 5: 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) |
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NEW QUESTION # 23
A company plans to implement Dynamics 365 Sales and wants to design a Dataverse data model that supports AI-driven insights across the sales lifecycle.
The company must be able to track the progression of a deal from initial prospect identification through to finalized billing.
The data model must support the following requirements:
. Prospects must be captured before they become qualified sales deals.
. Qualified deals must support forecasting and pipeline analysis.
. Sales teams must be able to generate pricing proposals for customers.
. Accepted proposals must transition into fulfillment records and then final billing records.
You need to design the Dataverse table model that supports the required sales lifecycle.
Which table relationship should you implement?
Answer: E
Explanation:
The correct sales lifecycle is Lead # Opportunity # Quote # Order # Invoice . In Dynamics 365 Sales, a lead captures an initial prospect before the person or organization is qualified. Microsoft's sales process guidance explains that sellers generally work with leads during the qualifying stage, and the goal is to qualify and advance the lead to the next stage of the sales process. Once qualified, the deal becomes an opportunity , which is the record used for pipeline tracking, revenue estimation, sales stages, probability, and forecasting analysis. Microsoft's prospect-to-quote guidance states that Dynamics 365 Sales supports capturing, managing, scoring, and converting leads into opportunities when qualification criteria are met.
Quotes are then created from opportunities to present pricing proposals to customers. Microsoft states that quotes created from opportunities are prefilled with opportunity details and products. Once the proposal is accepted, the quote can be converted into a sales order for fulfillment and then into an invoice for billing; Microsoft's quote/order/invoice process sample explicitly demonstrates converting an opportunity to a quote, a quote to a sales order, and a sales order to an invoice. Therefore, option B is the only sequence that correctly supports the full sales lifecycle.
References/topics: Lead management; opportunity pipeline; quote creation; order fulfillment; invoice billing; Dataverse Sales tables.
NEW QUESTION # 24
You are the Dynamics 365 Sales administrator for an electronics company.
The sales team is having difficulty locating different products in the same category -- for instance, all versions of flat screen TVs available.
You need to organize the products in a way that makes it easier for the sales team to search for products.
What should you use?
Answer: A
Explanation:
The correct answer is Product families because the requirement is to organize similar products into searchable categories. In Dynamics 365 Sales, product families are used to classify and group related products under a product hierarchy. Microsoft's product catalog guidance explains that products can be created as standalone products or inside a family depending on how the organization wants to organize and classify them, and the training module specifically describes creating product family hierarchies that include product bundles and individual products.
For the example in the question, "flat screen TV" would be the product family, while individual versions such as 42-inch, 55-inch, OLED, QLED, or 4K models would be products inside that family. This makes browsing and searching easier for sellers because related variants are grouped logically. Product unit groups define how products are sold, such as each, box, or case; they do not categorize products. Related products are used for cross-sell, upsell, substitute, or accessory recommendations, not primary catalog organization. Product bundles combine multiple products sold together as a package. Therefore, the correct catalog structure is Product families.
NEW QUESTION # 25
A company is using Dynamics 365 Sales.
The company is NOT using predictive lead scoring. The company has historical sales records for the last three years.
You need to configure a predictive lead scoring model.
What is the minimum number of records required?
Answer: C
Explanation:
The minimum dataset for a predictive lead scoring model is 40 qualified leads and 40 disqualified leads .
Microsoft's Dynamics 365 Sales documentation states that an organization must have created and closed at least 40 qualified and 40 disqualified leads within the selected training period to train the model. The broader lead and opportunity scoring documentation confirms the same threshold and distinguishes lead scoring from opportunity scoring: lead scoring requires qualified and disqualified leads, while opportunity scoring requires won and lost opportunities.
This distinction is critical. Predictive lead scoring predicts the likelihood that a lead will qualify or convert based on historical lead outcomes, so the model needs examples of both successful and unsuccessful lead qualification results. Won and lost opportunities are not the correct training records for lead scoring; they apply to predictive opportunity scoring. The question also states that the company has historical sales records for three years, but the model requirement is based on the minimum qualifying lead dataset, not merely the total age of available data. Therefore, the required minimum is 40 qualified leads and 40 disqualified leads .
References/topics: Predictive lead scoring; lead scoring model prerequisites; qualified leads; disqualified leads; AI-driven lead prioritization.
NEW QUESTION # 26
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.
You are deploying AI agents for a company using Microsoft Dynamics 365 Sales.
The company wants to ensure that AI usage is tracked and billed monthly.
The company requires that AI billing uses pre-paid credits.
You need to configure the billing based on the requirements.
Solution: Create an Azure subscription.
Does the solution meet the goal?
Answer: B
Explanation:
The solution does not meet the goal. Creating an Azure subscription is associated with pay-as-you-go billing scenarios, not the required pre-paid credits model. Microsoft's Dynamics 365 Sales agent billing guidance states that Sales Copilot and agent capabilities support two billing models: prepaid capacity and pay-as-you- go . Prepaid capacity uses Copilot Studio message pack subscriptions purchased in advance, while pay-as- you-go bills for actual message consumption during the month.
Because the requirement explicitly says AI billing must use pre-paid credits , the correct approach is to purchase Copilot Studio message packs or Copilot Credits and assign/manage that capacity for the relevant environment. Power Platform guidance explains that Copilot Studio credits/capacity are managed and monitored through the Power Platform admin center, and if prepaid capacity is exhausted, admins must reallocate capacity, purchase more credits, or enable pay-as-you-go. An Azure subscription may be required for pay-as-you-go cost management, but it does not satisfy a prepaid-credit requirement by itself. Therefore, the proposed solution is incorrect.
References/topics: Dynamics 365 Sales agent billing; prepaid capacity; Copilot Studio message packs; Copilot Credits; pay-as-you-go billing.
NEW QUESTION # 27
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 # 28
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