MB-910 Describe Dynamics 365 Customer Insights Practice Test 6 — 15 Questions

Question 1

Refer to the exhibit. A Customer Insights administrator creates a segment for high-value customers. Which customers will be included in this segment?

Accepted Answer

Customers with a CLV greater than 1000. The segment is defined as 'high-value customers,' and the rule shown in the exhibit filters for customers where Customer Lifetime Value (CLV) is greater than 1000. In Dynamics 365 Customer Insights, segments are built using conditions that evaluate numeric attributes, and the 'greater than' operator includes only records where the value exceeds the specified threshold.

Answer

All customers

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Customers with a CLV of exactly 1000

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Customers with a CLV less than 1000

Question 2

A retail company wants to unify customer data from their e-commerce platform, loyalty program, and in-store POS system to create a single customer view. Which Dynamics 365 tool should they use?

Accepted Answer

Dynamics 365 Customer Insights - Data. Dynamics 365 Customer Insights - Data is the correct tool because it is specifically designed to ingest, unify, and enrich customer data from multiple sources (e-commerce, loyalty, POS) into a single customer profile using identity resolution and data transformation pipelines. This creates a 360-degree view of the customer, which is the core requirement described in the question.

Answer

Dynamics 365 Customer Service

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Dynamics 365 Sales

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Dynamics 365 Customer Voice

Question 3

A marketing team wants to use AI to predict which customers are most likely to purchase a new product. Which feature of Dynamics 365 Customer Insights should they use?

Accepted Answer

Predictive models. Predictive models in Dynamics 365 Customer Insights use machine learning to analyze historical customer data and identify patterns that indicate a high likelihood of purchasing a new product. This feature allows the marketing team to create a binary prediction (e.g., will buy/will not buy) based on attributes such as past purchases, engagement, and demographics, directly addressing the need to predict which customers are most likely to purchase.

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Enrichment

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Measures

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Segmentation

Question 4

A company uses Dynamics 365 Customer Insights - Data to create a unified customer profile. They notice that duplicate records exist from different sources. What should they do to resolve this?

Accepted Answer

Configure deduplication rules within Customer Insights. D is correct because Dynamics 365 Customer Insights - Data provides built-in deduplication rules that allow you to define matching criteria (e.g., name, email, phone) to identify and merge duplicate records from different sources into a single unified customer profile. This is the intended, native mechanism for resolving duplicates within the system, ensuring data integrity without manual intervention or external tools.

Answer

Manually delete duplicate records in each source system

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Create a dataflow to filter duplicates

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Use Power Automate to remove duplicates

Question 5

A business analyst wants to create a segment of customers who have made a purchase in the last 30 days. Which Customer Insights component should they use?

Accepted Answer

Segmentation. Segmentation is the Customer Insights component specifically designed to create subsets of customers based on defined criteria, such as purchase recency. By setting a condition like 'purchase date within the last 30 days,' the business analyst can dynamically generate a segment of qualifying customers for targeted actions.

Answer

Predictive models

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Measures

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Enrichment

Question 6

A company wants to use Dynamics 365 Customer Insights to send personalized marketing emails based on customer behavior. Which integration is most appropriate?

Accepted Answer

Dynamics 365 Marketing. Dynamics 365 Marketing is the correct integration because it is purpose-built to orchestrate customer journeys and send personalized marketing emails based on behavioral data from Customer Insights. Customer Insights provides unified customer profiles and AI-driven insights, which Dynamics 365 Marketing consumes via real-time segmentation and triggers to deliver tailored communications.

Answer

Power Automate

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Power Apps

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Power BI

Question 7

A company uses Dynamics 365 Customer Insights - Data and wants to ensure that customer data from the EU complies with GDPR. What should they configure?

Accepted Answer

Data privacy settings within Customer Insights. Dynamics 365 Customer Insights - Data includes data privacy settings specifically designed to help meet GDPR requirements, such as data retention policies, consent management, and data subject rights (e.g., delete or export). Option A is incorrect because the Microsoft 365 compliance center is for broader compliance across Microsoft 365 services, not directly for Customer Insights data. Option B is incorrect because data classification labels in Microsoft Purview are used for labeling sensitive data across the organization, but they are not the specific configuration within Customer Insights for GDPR compliance. Option C is incorrect because DLP policies in Power Platform admin center govern data leakage prevention across Power Platform, but they do not address Customer Insights' specific privacy settings needed for GDPR.

Answer

Microsoft 365 compliance center

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Data classification labels in Microsoft Purview

Answer

Data loss prevention (DLP) policies in Power Platform admin center

Question 8

A marketing manager wants to see a 360-degree view of each customer, including their interactions, purchases, and support tickets. Which Dynamics 365 tool provides this?

Accepted Answer

Customer Insights - Data. Customer Insights - Data (option A) is the correct tool because it is specifically designed to unify customer data from multiple sources (e.g., interactions, purchases, support tickets) into a single, 360-degree customer view. It uses data ingestion, entity matching, and unification processes to create a comprehensive profile, directly addressing the marketing manager's requirement.

Answer

Dynamics 365 Field Service

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Dynamics 365 Customer Service

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Customer Insights - Journeys

Question 9

A company wants to use AI to calculate the likelihood that a customer will churn. Which Customer Insights feature should they use?

Accepted Answer

Predictive models. Predictive models in Dynamics 365 Customer Insights use machine learning to analyze historical customer data and calculate the likelihood of future outcomes, such as churn. This feature specifically builds a binary classification model that outputs a churn probability score for each customer, enabling proactive retention efforts.

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Measures

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Segmentation

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Enrichment

Question 10

A company has customer data in Salesforce, a SQL database, and Excel files. They need to bring all this data into Dynamics 365 Customer Insights. What should they use?

Accepted Answer

Customer Insights data ingestion connectors. Customer Insights data ingestion connectors are purpose-built to import data from external sources like Salesforce, SQL databases, and Excel files directly into Dynamics 365 Customer Insights. These connectors support a wide range of data sources and handle the extraction, transformation, and loading (ETL) process, enabling unified customer profiles without requiring custom development.

Answer

Dual-write

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Common Data Model

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Dataflows in Power Platform

Question 11

Which TWO of the following are capabilities of Dynamics 365 Customer Insights - Data?

Accepted Answer

Create a single, unified customer profile. Dynamics 365 Customer Insights - Data is specifically designed to create a single, unified customer profile by stitching together data from various sources. This unified profile provides a 360-degree view of each customer, enabling personalized engagement and analytics.

Answer

Create and manage marketing journeys

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Schedule field service appointments

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Create and manage sales quotes

Question 12

Which THREE of the following are data sources that can be ingested into Dynamics 365 Customer Insights - Data?

Accepted Answer

Salesforce. Dynamics 365 Customer Insights - Data supports ingesting data from Salesforce via its built-in Power Query connectors. This allows organizations to unify customer data from CRM systems like Salesforce into a single customer data platform (CDP) for 360-degree views.

Answer

Answer

SAP Concur

Question 13

Which TWO of the following are AI-powered features available in Dynamics 365 Customer Insights?

Accepted Answer

Predictive models for churn and purchase propensity. Dynamics 365 Customer Insights includes AI-powered predictive models that analyze historical customer data to forecast behaviors such as churn and purchase propensity. These models use machine learning algorithms to generate scores and insights directly within the Customer Insights platform, enabling proactive engagement strategies.

Answer

Email response sentiment analysis

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Lead scoring

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Anomaly detection in transaction data

Question 14

Refer to the exhibit. A customer has configured data unification in Customer Insights. What will happen when a contact from CRM and a member from Loyalty have the same email address?

Accepted Answer

The CRM contact data will take priority and overwrite Loyalty member data in the unified profile. The merge strategy is PriorityBased with CRM first, so the CRM record takes precedence. Option B is wrong because a new unified profile is not created; instead, the existing CRM profile is enriched with data from the Loyalty record. Option C is wrong because the system automatically resolves matches based on the configured priority, not manual intervention. Option D is wrong because fields are not merged equally; the priority-based strategy means the CRM record's data overwrites the Loyalty member's data in the unified profile.

Answer

A new unified profile will be created with a new ID

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The system will prompt the user to manually resolve the match

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All fields from both records will be merged equally

Question 15

Refer to the exhibit. A data analyst runs this KQL query in Customer Insights. What is the purpose of this query?

Accepted Answer

To calculate the total purchase amount for a specific customer. The KQL query shown in the exhibit uses the `sum()` aggregation function on the `PurchaseAmount` column, filtered by a specific `CustomerID`. This calculates the total purchase amount for that single customer. Option C is correct because the query explicitly sums purchase amounts for one customer, not for a segment or as a predictive model.

Answer

To predict the likelihood of a customer making a future purchase

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To create a segment of customers with high purchase amounts

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To create a measure that calculates average purchase amount