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

Question 1

An administrator notices that customer profiles in Dynamics 365 Customer Insights have duplicate records after data unification. What should they do to resolve this?

Accepted Answer

Adjust the deduplication rules. Option D is correct because deduplication rules in Dynamics 365 Customer Insights define how the system identifies and merges duplicate records during data unification. If duplicates remain after unification, adjusting these rules—such as modifying match conditions, similarity thresholds, or priority order—allows the system to correctly consolidate duplicate customer profiles without losing data or requiring a full re-run.

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Add a custom field

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Delete one of the data sources

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Re-run data unification

Question 2

A marketing team wants to send a promotional email to customers who have a high likelihood of purchasing a new product. Which Dynamics 365 Customer Insights feature should they use?

Accepted Answer

Use a prediction model for purchase propensity. A prediction model for purchase propensity uses machine learning to analyze customer signals (e.g., browsing history, past purchases, demographics) and assign a probability score indicating how likely each customer is to buy a new product. This directly meets the marketing team's need to target high-likelihood customers, as it goes beyond simple historical data to predict future behavior.

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Define a measure of average spend

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Create a segment based on past purchases

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Run data unification

Question 3

A company wants to combine data from Microsoft 365, Dynamics 365, and their custom app into one customer data platform. Which Dynamics 365 Customer Insights capability enables this?

Accepted Answer

Data ingestion and unification. Option D is correct because data ingestion allows connecting various data sources. Option A is wrong because segments are subsets. Option B is wrong because measures are KPIs. Option C is wrong because predictions are models.

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Measures

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Customer segments

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Prediction models

Question 4

A business analyst wants to create a KPI that shows the average customer lifetime value for customers acquired in the last year. Which Dynamics 365 Customer Insights feature should they use?

Accepted Answer

Define a measure. A measure in Dynamics 365 Customer Insights is used to calculate numeric KPIs from your customer data, such as average customer lifetime value (CLV) for a specific cohort. By defining a measure with a filter for customers acquired in the last year, you can compute the exact average CLV without needing predictive models or data transformation steps.

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Create a prediction model

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Run data unification

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Create a segment of recent customers

Question 5

A company wants to provide customer service agents with a 360-degree view of the customer including recent interactions, purchases, and sentiment. Which Dynamics 365 Customer Insights feature should they use?

Accepted Answer

Unified customer profile. The unified customer profile in Dynamics 365 Customer Insights aggregates data from multiple sources (e.g., sales, service, marketing) into a single, 360-degree view of each customer. This includes recent interactions, purchase history, and sentiment scores, enabling agents to see the complete customer journey. The other options focus on analytics or grouping, not on providing a holistic, real-time profile.

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Prediction models

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Measures

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Segments

Question 6

Which TWO data sources can be used to ingest data into Dynamics 365 Customer Insights? (Choose two.)

Accepted Answer

Power Query. Power Query is a native data ingestion tool within Dynamics 365 Customer Insights that allows users to connect to a wide variety of data sources, transform data using a graphical interface, and load it into the Customer Insights data lake. It supports connectors for databases, online services, and files, making it a primary method for importing customer data.

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Azure DevOps

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Excel file

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Microsoft Teams

Question 7

Which THREE actions can be performed using Dynamics 365 Customer Insights? (Choose three.)

Accepted Answer

Predict customer churn. Options A, B, and D are correct. Customer Insights can unify customer data, create segments, and generate predictions. Option C is wrong because it doesn't manage IT devices. Option E is wrong because it doesn't design marketing emails; that is done in Dynamics 365 Marketing.

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Manage IT device compliance

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Design email marketing campaigns

Question 8

Which TWO are benefits of using Dynamics 365 Customer Insights? (Choose two.)

Accepted Answer

Gain a single view of the customer. Option A is correct because Dynamics 365 Customer Insights unifies customer data from multiple sources (e.g., transactional, behavioral, and demographic) into a single, 360-degree view using its data unification and matching capabilities. This enables organizations to understand their customers holistically without data silos.

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Automate supply chain processes

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Manage financial transactions

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Manage customer service cases

Question 9

An administrator is configuring a data source in Dynamics 365 Customer Insights using the provided JSON. What is the purpose of this configuration?

Accepted Answer

To ingest data from Dynamics 365. The JSON configuration defines a data source connection to Dynamics 365, specifying the entity and field mappings required to ingest data into Customer Insights. This is the foundational step for bringing customer data into the system for unification, enrichment, and analysis.

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To run a prediction model

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To create a customer segment

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To calculate a measure

Question 10

A data engineer is reviewing the unification configuration in Dynamics 35 Customer Insights. What does this configuration accomplish?

Accepted Answer

Matches customer records by exact email. Option D is correct because the matching rule uses exact match on the email field to unify records. Option A is wrong because it doesn't segment. Option B is wrong because it doesn't create predictions. Option C is wrong because it doesn't calculate measures.

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Calculates average revenue

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Predicts customer churn

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Creates a segment of customers with email

Question 11

A marketer creates a segment in Dynamics 365 Customer Insights using the JSON shown. What will this segment contain?

Accepted Answer

Customers who have spent more than $10,000. Option B is correct because the JSON segment definition includes a condition that filters customers based on 'totalSpend' being greater than 10000. In Dynamics 365 Customer Insights, segments are built using attribute-based rules, and this JSON explicitly defines a numeric comparison on the 'totalSpend' field, which directly corresponds to customers who have spent more than $10,000.

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Customers with low spending

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Customers likely to churn

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New customers acquired this month

Question 12

A retail company uses Dynamics 365 Customer Insights to unify customer data from online and in-store transactions. They want to define a customer segment based on customers who have made a purchase within the last 30 days and have a lifetime value above $500. Which feature should they use?

Accepted Answer

Create a segment based on conditions. Option A is correct because Dynamics 365 Customer Insights allows you to define a segment based on conditions, such as combining a purchase recency filter (last 30 days) with a calculated lifetime value threshold (>$500). This uses the segment builder's rule-based logic to query unified customer profiles and transactional data, enabling precise targeting without custom code.

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Create a measure

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Enrich customer profiles with demographic data

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Create a prediction model

Question 13

A company is using Dynamics 365 Customer Insights to get a unified view of their customers. They have data from their e-commerce platform, CRM system, and customer support tickets. Which step is required to ensure that the same customer is recognized across these different data sources?

Accepted Answer

Configure data matching rules. B is correct because data matching rules in Dynamics 365 Customer Insights define how records from different sources (e-commerce, CRM, support tickets) are identified as belonging to the same customer. These rules use conditions like email, phone, or name to deduplicate and unify customer profiles into a single entity, ensuring consistent recognition across all ingested data sources.

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Enrich profiles with external data

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Create measures and KPIs

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Set up data export destinations

Question 14

A marketing team uses Dynamics 365 Customer Insights to create segments for targeted campaigns. They have a segment of 'High Value Customers' defined as those with a lifetime value in the top 20%. After a recent campaign, they want to evaluate the return on investment (ROI) for this segment. Which feature should they use to measure the campaign's impact on these customers?

Accepted Answer

Use the built-in measures and analytics to compare segment performance before and after the campaign. Option C is correct because Dynamics 365 Customer Insights provides built-in measures and analytics that allow you to compare key performance indicators (KPIs) for a segment before and after a campaign. This directly enables ROI calculation by measuring changes in metrics like revenue or engagement specifically for the 'High Value Customers' segment, without needing external data ingestion or predictive models.

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Ingest campaign interaction data from external sources

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Enrich profiles with demographic data

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Build a churn prediction model

Question 15

A company is planning to implement Dynamics 365 Customer Insights. They have customer data stored in an on-premises SQL Server database and also in Salesforce CRM. They want to unify this data in Customer Insights. Which data ingestion method should they use to bring data from both sources?

Accepted Answer

Use Power Query with a gateway for on-premises SQL and the Salesforce connector for Salesforce. Option B is correct because Dynamics 365 Customer Insights uses Power Query as its primary data ingestion engine, which supports both on-premises SQL Server via an on-premises data gateway and cloud-based Salesforce CRM through a dedicated Salesforce connector. This allows the company to unify data from both sources without requiring intermediate storage or third-party tools.

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Use Power Query connectors for cloud data only, then use a gateway for on-premises SQL

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Export data from SQL to Azure Blob Storage and then ingest from Blob, and use Salesforce API

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Use third-party ETL tool to push data into Customer Insights via API