Microsoft AB-210 Exam Dumps

The correct configuration is Sales Qualification Agent in Research and engage mode. The question contains one conflicting sentence about human-managed outreach, but the explicit agent requirements require autonomous outreach, response handling, BANT evaluation, positive-intent detection, disqualification of poor-fit leads, supervisor notification, and seller handoff. Those capabilities map only to Research and engage mode.

Microsoft's Sales Qualification Agent documentation states that both modes can research leads and check target customer profile fit, but only Research and engage mode checks BANT criteria, sends outreach emails, detects positive intent, sends follow-up emails, and engages with leads based on their responses. Microsoft's handoff criteria documentation also states that BANT criteria are only used by Research and engage mode, and that leads satisfying BANT and purchase-interest criteria are handed over to sellers, while leads that do not satisfy the configured criteria are disqualified and added for supervisor review.

Option B or D would be correct only if the controlling requirement were strictly ''human sellers must manage all outreach.'' But the listed automation requirements go beyond Research-only mode, so the exam answer is C.

References/topics: Sales Qualification Agent; Research and engage mode; target customer profile; BANT; purchase intent; lead handoff; supervisor review.

The correct outcome is that the agent disqualifies the lead, notifies the supervisor, and the lead continues to be assigned to the agent. In Research-only mode, the Sales Qualification Agent evaluates whether the lead fits the target customer profile. Microsoft states that when target customer profile suitability is high or medium, the lead is handed over to a seller according to the configured assignment rule. When target customer profile suitability is low, the agent disqualifies the lead, notifies the supervisor, and the lead remains assigned to the agent.

Option A is wrong because Research-only mode does not always transfer every lead to a seller; low-fit leads can be disqualified. Option C describes Research and engage behavior, where the agent sends outreach, manages responses, and hands over leads when positive intent is detected. Research-only mode generates outreach drafts but does not send outreach emails or engage with leads. Option D is also wrong because BANT criteria are only used by Research and engage mode, not Research-only mode. Therefore, a low target customer profile suitability result in Research-only mode results in agent disqualification and supervisor notification.

References/topics: Sales Qualification Agent; Research-only mode; target customer profile suitability; lead disqualification; supervisor notification; lead handoff rules.

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.

Yes, the solution meets the goal. The requirement is very specific: sales managers need deal insights, but the organization must avoid automatic outreach to buyers. Sales Close Agent in Research mode is the correct configuration because it focuses on researching opportunities, analyzing deal context, identifying risks and signals, and providing recommendations to sellers without autonomously engaging customers.

Research mode is intended to help sellers understand an opportunity more quickly by surfacing insights such as deal health, signals, risks, and suggested next actions. It supports opportunity management by giving the team intelligence that can help progress deals, while leaving communication decisions in the hands of the seller. That directly aligns with the stated requirement for insights about deals.

The critical distinction is that Engage mode is the mode that performs automated outreach and customer interaction. Since the company explicitly does not want automatic outreach to buyers, Engage mode would violate the requirement. By configuring the Sales Close Agent in Research mode, the company gets AI-assisted opportunity analysis without autonomous communications.

References/topics: Sales Close Agent; Research mode; opportunity insights; deal analysis; recommended next actions; distinction between Research mode and Engage mode.

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.