The correct answer is D. Opportunities that use the expired price list can continue through their lifecycle. In Dynamics 365 Sales, a price list can include a Start Date and End Date to define the effective period for that price list, such as a promotional pricing period. Microsoft’s pricing guidance explains that price lists and price list items define pricing for products, and that price calculation applies across opportunity, quote, order, and invoice records.

The expiration date controls the effective availability of the price list going forward; it does not automatically invalidate existing opportunity records that already reference that price list. This distinction matters operationally: if an opportunity was already created with a valid price list, the sales process can continue without forcing users to replace pricing midstream. That preserves pricing consistency across the opportunity lifecycle and prevents disruption to quotes, orders, and downstream sales documents.

Option A is too strong because Dynamics 365 does not require replacement of prices simply because the referenced price list later expires. Option B incorrectly limits use based on the creation date of the opportunity. Option C is not the best answer because the key supported behavior is continuation of existing opportunities, not adding expired price lists to new opportunities with a warning.

References/topics: Price lists; price list start and end dates; opportunity pricing; product catalog pricing; opportunity lifecycle management.

Requirement

Configuration

Blueprints

Name the blueprint workspace and pin the workspace.

Questions

Create a business function with seeded prompts.

For Blueprints, the correct configuration is to name the blueprint workspace and pin the workspace. The requirement is not asking to regenerate analysis; it asks for a reliable way to return to frequently used research output. In Sales Research Agent, a generated blueprint exists inside a workspace, and Microsoft states that the workspace displays the workspace name, can be renamed, and can be switched from the workspace menu. That makes naming and pinning the workspace the correct operational pattern for reusable research access.

For Questions, the correct configuration is to create a business function with seeded prompts. Sales Research Agent business functions are designed to tailor research to a specific use case, and administrators can add starter prompts. Microsoft explains that starter prompts appear on the Sales Research Agent home page for quick access and that the full prompt is sent to the agent when selected. This directly satisfies the requirement to retain a reusable library of approved questions.

Do not select regenerate the blueprint because regeneration refreshes or recreates analysis, but it does not create a persistent shortcut to frequently used research. Do not select custom table or manual prompt questions in Sales Copilot because the native Sales Research Agent feature already supports reusable business-function prompts.

References/topics: Sales Research Agent; research blueprints; workspace management; business functions; seeded/starter prompts; intelligent opportunity research.

The correct answer is Rounding Amount . In Dynamics 365 Sales price list item configuration, rounding is used when calculated prices must follow a specific price-ending convention, such as ending in .98 or .99 . Microsoft’s pricing guidance explains that price list items can use rounding behavior so calculated product prices can be rounded and made to end in a specified amount, such as 99 cents. The value that defines the exact ending amount is the Rounding Amount . Therefore, to make all calculated prices end in $.98 , the administrator would configure the rounding amount as 0.98 .

Rounding Policy is not precise enough by itself. It controls the direction of rounding, such as rounding up, down, or to the nearest value, but it does not define the exact cents-ending requirement. Pricing Method determines how the price is calculated, such as a currency amount, percentage of list price, markup, or margin. Percentage is used when a percentage-based pricing method is selected, but it does not force prices to end in $.98 . The requirement is explicitly about the final rounded price ending, so Rounding Amount is the correct function.

References/topics: Price lists; price list items; rounding amount; rounding policy; Dynamics 365 Sales product pricing.

Issue

Action

Opportunity updated today is NOT included in the chart

Update roll-up settings

Time period for the goal is inaccurate

Have the manager update the goal

For the opportunity updated today not appearing in the goals chart, the issue is the goal rollup timing , not the opportunity record itself. Dynamics 365 Sales goal actuals are calculated through rollup processing. Microsoft states that automatic goal rollup duration and frequency are controlled from the Goals tab in system settings, and that manual rollup can also be performed when needed. Therefore, the correct action is to update the roll-up settings so goal charts reflect recent opportunity changes more appropriately. Microsoft also notes that selecting Recalculate updates goal actuals based on the latest data, confirming that goal charts depend on rollup recalculation rather than instant real-time updates.

For the inaccurate goal time period, the correct action is to have the manager update the goal . In Dynamics 365 Sales goal management, the goal manager is responsible for setting or modifying goal targets, adjusting the goal time period, and assigning the goal owner. The salesperson is typically the goal owner who is measured against the target, but the manager controls the goal definition and period.

References/topics: Dynamics 365 Sales goals; goal rollup settings; goal recalculation; goal manager responsibilities; opportunity target tracking.

The Sales Close Agent in Research mode is the correct fit for assessing opportunity risk and prioritizing opportunities that are gaining traction. Microsoft’s AI agents guidance states that the opportunity-focused sales agent helps sellers close deals faster by autonomously researching opportunities, providing visibility into emerging risks, and highlighting promising opportunities. It is designed to identify high-value and at-risk opportunities so sellers can prioritize their effort and act on critical insights.

The Sales Close Agent in Engage mode is the correct fit for recommending opportunity products to clients automatically. Microsoft describes Sales Close Agent as an autonomous agent for high-velocity sales execution that engages customers, recommends products, handles objections, and drives transactions toward closure using configured product catalog and pricing information.

The Sales Qualification Agent is not appropriate for these scenarios because it is lead-focused, not opportunity-focused. It researches inbound leads, evaluates fit, generates outreach, and can hand promising leads to sellers depending on the configured mode. It does not manage opportunity risk, opportunity traction, or client product recommendations for active deals.

References/topics: Sales Close Agent; opportunity research; opportunity risk; opportunity prioritization; Sales Close Agent Engage mode; product recommendations.

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.

Requirement

Configuration

Automatically prioritize leads based on conversion probability

Predictive lead scoring

Ensure the lead scoring improvement requirement is met

Automatically retrain model

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.

References/topics: Predictive lead scoring; lead prioritization; scoring model accuracy; automatic model retraining; AI-driven lead qualification.

Requirement

Component

Mountaineer range

Product family

Athlete package

Product bundle

Metal range

Product property

The Mountaineer range should be configured as a Product family because it represents a product classification hierarchy. Dynamics 365 Sales uses product families to organize related products, child products, and bundles under a parent structure. Microsoft’s product catalog guidance states that product families can contain child product families, products, and bundles in a hierarchy, which fits the mountaineer cycle range with economy and premium fitting variations.

The Athlete package should be configured as a Product bundle because it combines multiple sellable items: a cycle, connected devices, and subscription-based analytics services. A bundle is used when multiple products are sold together as one commercial package. Dynamics 365 Sales allows products to be associated with a bundle, including quantities and required or optional components.

The Metal range should be configured as a Product property because sellers must choose a configurable attribute—chrome, aluminum, or titanium—when adding the mountaineer cycle to an opportunity. Product properties define product characteristics such as size, color, or component, and can be used at run time when adding products to opportunities, quotes, orders, or invoices.

References/topics: Product catalog setup; product families; product bundles; product properties; opportunity product configuration.

For Dynamics 365 Sales predictive lead scoring, the model cannot be created unless there is enough historical lead outcome data in the selected training window. Microsoft’s predictive lead scoring configuration requirement states that the organization must have at least 40 qualified leads and 40 disqualified leads in the selected training period. The official guidance specifically explains that if the model is trained with leads from the past three months, the organization needs “at least 40 qualified and 40 disqualified leads” created and closed during that period.

In the sandbox, AdventureWorks has 30 qualified leads and 20 disqualified leads. However, 10 of the qualified leads are older than three months, and the business requirement says predictive scoring must be enabled for leads created within the last three months. Therefore, only 20 qualified leads are usable for this model. The sandbox currently has 20 usable qualified leads and 20 disqualified leads. To meet the required threshold of 40 each, the company needs 20 more qualified leads and 20 more disqualified leads . Simply creating 40 new leads is not enough because predictive scoring requires outcome-classified leads, not merely open or newly created records.

References/topics: Configure predictive lead scoring; lead scoring model training data requirements; AI-driven lead prioritization in Dynamics 365 Sales.

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.