MB-910 Describe Dynamics 365 Customer Insights Practice Test 11 — 15 Questions

Question 1

A small business wants to unify customer data from their online store, email list, and social media interactions using Dynamics 365 Customer Insights. They have limited technical resources. What is the recommended first step?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Ingest data from their existing sources and configure match rules. The recommended first step in Dynamics 365 Customer Insights is to unify customer data by ingesting data from all existing sources (online store, email list, social media) and configuring match rules to identify unique customers across those sources. This creates the unified customer profile, which is the foundational prerequisite for any segmentation, measures, or enrichment. Without ingesting and matching data, no other feature can function. This aligns with the standard implementation approach for Customer Insights.

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Build segments based on customer location

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Create measures to calculate key performance indicators

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Enrich profiles with demographic data from a third-party provider

Question 2

A healthcare provider uses Dynamics 365 Customer Insights to manage patient profiles. They need to ensure that only authorized users can access sensitive health information. Which feature should they configure?

Accepted Answer

Role-based access control (RBAC). Role-based access control (RBAC) in Dynamics 365 Customer Insights allows administrators to assign specific permissions (e.g., read, write, delete) to users based on their roles, ensuring that only authorized personnel can access sensitive health information. This is the primary mechanism for securing patient data and complying with regulations like HIPAA.

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Enrichment with external data

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Match rules for deduplication

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Data source connections

Question 3

Which TWO activities are part of the data unification process in Dynamics 365 Customer Insights?

Accepted Answer

Configuring match rules to identify duplicates. Configuring match rules is a core step in the data unification process in Dynamics 365 Customer Insights. Match rules define the conditions (e.g., fuzzy matching on email or phone) used to identify duplicate customer records across source systems, enabling deduplication and merging into a single unified profile. This is distinct from segmentation or enrichment, which occur after unification.

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Creating segments based on customer attributes

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Defining measures for customer metrics

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Enriching profiles with external data

Question 4

Which TWO are best practices when configuring match rules in Dynamics 55 Customer Insights?

Accepted Answer

Combine exact and fuzzy matching for better coverage. Combining exact and fuzzy matching in Dynamics 365 Customer Insights allows the system to identify both identical records (exact match) and near-duplicates with minor variations like typos or abbreviations (fuzzy match), improving deduplication coverage without sacrificing precision. This hybrid approach is a best practice to balance accuracy and recall when configuring match rules.

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Use only exact matching to ensure no false positives

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Create as many match rules as possible to capture all duplicates

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Disable deduplication for high-volume data sources

Question 5

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 profile. Which Dynamics 365 Customer Insights capability should they use?

Accepted Answer

Data unification. Data unification is the correct capability because it is specifically designed to reconcile and merge customer records from disparate data sources—such as e-commerce platforms, loyalty programs, and POS systems—into a single, unified customer profile. This process uses matching rules, deduplication, and conflict resolution to create a 360-degree view of each customer, which is the core requirement described in the question.

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Power BI integration

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Marketing segmentation

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Customer Voice

Question 6

A company wants to predict which customers are likely to churn in the next 30 days using historical data and AI. Which feature in Dynamics 365 Customer Insights should they use?

Accepted Answer

Predictions. The Predictions feature in Dynamics 365 Customer Insights uses prebuilt AI models to analyze historical customer data and calculate churn probability scores for a specified future period, such as the next 30 days. This directly addresses the requirement to predict which customers are likely to churn, as it leverages machine learning to identify patterns and generate actionable insights without requiring custom model building.

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Segmentation

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Measures

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Copilot

Question 7

A marketing team wants to send personalized email campaigns based on customer lifetime value (CLV) scores. They have already built a CLV prediction model in Customer Insights. What is the next step to use these scores in a marketing campaign?

Accepted Answer

Create a segment based on the CLV prediction in Customer Insights. In Dynamics 365 Customer Insights, predictions like CLV are stored as data entities. To use them in a marketing campaign, you must first create a segment that filters customers based on the CLV prediction score. This segment can then be exported or used directly in Dynamics 365 Marketing journeys. Option A is correct because segments are the bridge between Customer Insights data and Marketing campaign targeting.

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Use the prediction directly in a Marketing journey

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Use Power BI to visualize the CLV scores

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Export the CLV scores to Excel and import into Dynamics 365 Marketing

Question 8

A business analyst wants to create a measure that calculates the average order value for customers. Where in Dynamics 365 Customer Insights would they define this calculation?

Accepted Answer

Measures. In Dynamics 365 Customer Insights, measures are used to define calculated metrics such as average order value. Measures aggregate data from your data sources using formulas (e.g., SUM, AVERAGE) and are stored as KPIs that can be used in segments, insights, or dashboards. This is the correct location for defining custom calculations like average order value.

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Data sources

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Segments

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Predictions

Question 9

A customer data platform administrator notices that duplicate customer records appear after unification. They want to review and adjust the matching rules. Where in Customer Insights can they do this?

Accepted Answer

Data unification. In Dynamics 365 Customer Insights, the matching rules that determine how duplicate customer records are identified and merged during the unification process are configured within the Data unification section. Specifically, after selecting data sources and mapping fields, the administrator defines match conditions (e.g., exact or fuzzy matching on email, phone) under the 'Match' step. Adjusting these rules directly controls how duplicates are detected and resolved during unification.

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Duplicate detection

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Data sources

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Admin settings

Question 10

A company wants to provide customer service agents with a 360-degree view of customers, including purchase history and support interactions. Which Dynamics 365 application can consume Customer Insights unified profiles?

Accepted Answer

Dynamics 365 Customer Service. Dynamics 365 Customer Service can consume Customer Insights unified profiles to provide agents with a 360-degree view of customers, including purchase history and support interactions. This integration enriches the service experience by surfacing unified customer data directly within the agent interface, enabling personalized and context-aware support.

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Dynamics 365 Human Resources

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Dynamics 365 Finance

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Dynamics 365 Project Operations

Question 11

A marketing manager wants to use AI to generate personalized content for email campaigns based on customer preferences. Which feature in Customer Insights should they use?

Accepted Answer

Copilot. Copilot in Dynamics 365 Customer Insights uses generative AI to create personalized content, such as email copy, based on customer preferences and data. It directly addresses the marketing manager's need to generate tailored content without manual effort, leveraging natural language prompts and customer insights.

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Predictions

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Segmentation

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Measures

Question 12

Which TWO actions are performed during the data unification process in Dynamics 365 Customer Insights?

Accepted Answer

Merging duplicate records into a single profile. The data unification process in Dynamics 365 Customer Insights includes deduplication, where duplicate records from the same or different sources are merged into a single, unified customer profile. This step ensures that each customer is represented once, eliminating fragmentation and providing a single source of truth.

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Enriching profiles with external demographic data

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Creating measures to calculate KPIs

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Creating segments for marketing campaigns

Question 13

Which TWO features are available in Dynamics 365 Customer Insights to help understand customer behavior?

Accepted Answer

Predictions. D is correct because the Predictions feature in Dynamics 365 Customer Insights uses built-in AI models to analyze historical customer data and forecast behaviors such as churn, conversion likelihood, and next best action. This directly helps organizations understand and anticipate customer behavior without requiring custom machine learning development.

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Admin settings

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Data sources

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Data unification

Question 14

You are reviewing the activity mapping configuration. The source system is Salesforce, and the target is Customer Insights. The mapping specifies that the CustomerId field is mapped from AccountId. What is the purpose of this mapping?

Accepted Answer

To specify which field in Salesforce corresponds to the customer identifier in the activity. Option D is correct because activity mapping in Customer Insights uses a source field (here Salesforce's AccountId) to identify which customer profile the activity belongs to, so the mapping tells the system which Salesforce field supplies the customer identifier for the activity record. The CustomerId field in the target is thus populated from AccountId to link the activity to the right unified customer. Option A is wrong because relationship definitions between source and Customer Insights profiles are configured separately, not through an activity field mapping. Option B is wrong because the mapping goes from AccountId to CustomerId, not from UnifiedCustomerId to AccountId. Option C is wrong because this mapping does not create a new Purchase activity-to-Customer entity relationship; it only specifies the source field used as the customer identifier.

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To define the relationship between Salesforce and Customer Insights customer profiles

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To map the UnifiedCustomerId to the Salesforce AccountId

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To create a new relationship between the Purchase activity and the Customer entity

Question 15

You are configuring a match rule for data unification. What does this rule specify?

Accepted Answer

Records with the exact same email address are considered a match. In Dynamics 365 Customer Insights, a match rule defines the conditions under which two or more records are considered to represent the same entity (e.g., a customer). Specifying that records with the exact same email address are considered a match is a common and valid rule, as email addresses are typically unique identifiers. The rule uses exact matching logic, not fuzzy or similarity-based matching, to determine duplicates during data unification.

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Records with the same CustomerId are considered a match

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Records with the same name are considered a match

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Records with similar email addresses are considered a match