Pass the Microsoft Certified: Dynamics 365 Sales AI Consultant Associate AB-210 Questions and answers with Dumpstech

Requirement

Configuration

Filter leads for assignment

Create a segment to filter the lead source. Add country/region as an additional condition.

Assign the country/region to the correct group

Assign the country/region to sellers with matching attributes.

Distribute leads to salespeople

Use load balancing.

The clean configuration is to create one reusable segment for webform leads, then add the varying country/region condition inside each country-specific assignment rule. Dynamics 365 Sales assignment rules are built by selecting the eligible segment first, then adding rule conditions to further filter records. Microsoft also recommends splitting conditions between segments and assignment rules to keep rules simpler and more efficient.

For routing to the correct sellers, use sellers with matching attributes . The scenario says salespeople manage leads by country/region and that a country/region attribute has been created. Assignment rules support assigning records to sellers who satisfy matching seller attributes or existing seller record fields, which avoids hardcoding individual sellers and is much easier to maintain as sellers change regions.

For distribution, use load balancing because the requirement is capacity-based: no seller should exceed 20 open leads. Dynamics 365 Sales load balancing distributes records based on seller workload/capacity, and seller capacity is calculated by subtracting active assigned records from the maximum configured capacity. Round robin is weaker here because it primarily considers assignment order, not workload.

References/topics: Sales accelerator work assignment; segments; lead assignment rules; seller attributes; seller capacity; load balancing.

Parameter

Option

Entity

Opportunity

Date field

Actual Close Date

Revenue field

Actual Revenue

The correct table is Opportunity because the goal measurement is based on deal amounts when opportunities are closed. In Dynamics 365 Sales goal metrics, rollup fields define which table and source attribute are used to calculate actual or in-progress goal values. Microsoft’s goal metric documentation gives the direct example of using the Opportunity table with the opportunity actual value/source attribute to track actual money amounts from opportunities closed as Won .

The correct date field is Actual Close Date because the goal period must be determined by when the deal was actually closed, not when the opportunity was created. Microsoft’s goal metric configuration guidance states that the Date Field determines the goal period that records roll up into, and gives Actual Close Date as the relevant example.

The correct revenue field is Actual Revenue because the requirement is based on the total deal amount upon closing the opportunity. Budget Amount and Total Amount do not represent the final closed deal value for goal actuals. Goal rollup fields calculate actual performance values for completed measurable results, which fits closed opportunity revenue.

References/topics: Dynamics 365 Sales goals; goal metrics; rollup fields; opportunity actual revenue; actual close date; sales performance tracking.

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.

No, the solution does not meet the goal. The requirement clearly states that sales managers need insights about deals , but the system must not perform automatic outreach to buyers . Sales Close Agent Engage mode is designed for autonomous customer engagement. It can interact with buyers, send outreach or follow-up communications, and help progress sales conversations automatically. That violates the restriction in the question.

For this scenario, the appropriate configuration is Sales Close Agent in Research mode , not Engage mode. Research mode supports opportunity management by analyzing deal context, surfacing risks, identifying signals, and providing recommended next actions to sellers. It gives managers and sellers AI-generated deal insights while keeping buyer communication under human control. That is exactly what the company requires.

Engage mode would only be acceptable if the company wanted the agent to actively contact buyers or automate customer-facing communication. Since the requirement explicitly prohibits automatic outreach, Engage mode fails the stated goal.

References/topics: Sales Close Agent; Research mode versus Engage mode; opportunity insights; deal risk analysis; AI-assisted opportunity management without autonomous outreach.

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.

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 .

References/topics: Product catalog setup; product families; product classification; product hierarchy; Dynamics 365 Sales core product configuration.

The correct two UI elements are the Select record type dropdown and one of the Customize field dropdowns on the work item card. In Dynamics 365 Sales, a “company” record is represented by the Account table. The screenshot currently shows the selected record type as Contacts , which would expose contact-related fields such as Full Name, Job Title, and Company Name. That is not the correct entity if the requirement is to display the industry of a company. Therefore, the record type must first be changed to Accounts .

After selecting Accounts , modify the card layout by selecting the Industry field in the Customize section. Microsoft’s sales accelerator workspace guidance states that work item appearance can be customized for each record type so sellers see the most relevant information in their work list. The work item appearance page lets administrators choose the record type and configure the fields displayed on the work item card.

Do not modify Lock customization as the answer target. That controls whether users can personalize the layout; it does not select the account entity or display the Industry field.

References/topics: Sales accelerator workspace; work item appearance; account record type; field customization; seller work list configuration.

The correct actions are to enable server-side synchronization and approve the users’ mailboxes . This is a very specific Dynamics 365 Sales mobile prerequisite. Microsoft’s Sales mobile setup guidance states that to set a regarding record for a meeting, server-side synchronization must be enabled in the environment and the email address must be approved. The mobile meeting documentation repeats the same requirement: users can set the regarding record only when server-side synchronization is enabled and the email address is approved.

This makes options A and B the only correct pair. Server-side synchronization connects Dynamics 365 with Exchange/Outlook data for appointments, contacts, tasks, and email synchronization. Microsoft’s server-side synchronization documentation describes it as the synchronization mechanism between customer engagement apps and Exchange, including support for appointments and mobile scenarios. A mobile offline profile controls offline data availability, not whether Outlook meetings can be tracked to customer records. Relevance search improves search behavior and performance, but it does not enable the Regarding field for meetings.

References/topics: Dynamics 365 Sales mobile app; meeting tracking; Regarding record; server-side synchronization; mailbox approval; Outlook appointments.

Parameter

Option

Entity

Opportunity

Date field

Actual Close Date

Revenue field

Actual Revenue

The correct table is Opportunity because the goal measurement is based on deal amounts when opportunities are closed. In Dynamics 365 Sales goal metrics, rollup fields define which table and source attribute are used to calculate actual or in-progress goal values. Microsoft’s goal metric documentation gives the direct example of using the Opportunity table with the opportunity actual value/source attribute to track actual money amounts from opportunities closed as Won .

The correct date field is Actual Close Date because the goal period must be determined by when the deal was actually closed, not when the opportunity was created. Microsoft’s goal metric configuration guidance states that the Date Field determines the goal period that records roll up into, and gives Actual Close Date as the relevant example.

The correct revenue field is Actual Revenue because the requirement is based on the total deal amount upon closing the opportunity. Budget Amount and Total Amount do not represent the final closed deal value for goal actuals. Goal rollup fields calculate actual performance values for completed measurable results, which fits closed opportunity revenue.

References/topics: Dynamics 365 Sales goals; goal metrics; rollup fields; opportunity actual revenue; actual close date; sales performance tracking.

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.