MB-910 Practice Exam 54 — 20 Questions

Question 1

A retail company wants to create a single view of each customer by unifying data from their e-commerce platform, in-store POS system, and loyalty program. Which Dynamics 365 Customer Insights capability should they use?

Accepted Answer

Customer Data Platform (CDP) capabilities. The correct answer is B because Dynamics 365 Customer Insights is a Customer Data Platform (CDP) that ingests, unifies, and resolves customer data from multiple sources—such as e-commerce platforms, POS systems, and loyalty programs—into a single, unified customer profile. This capability is specifically designed to create a 360-degree view of each customer by matching and merging records across disparate data sources.

Answer

Connections

Answer

Predictions

Answer

Segmentation

Question 2

A marketing team wants to use Customer Insights to predict which customers are likely to purchase a new product within the next 30 days. They have historical purchase data, web browsing behavior, and demographic data. What type of prediction should they create?

Accepted Answer

Custom model (binary classification). Option C is correct because the marketing team needs to predict a binary outcome (will purchase vs. will not purchase) within a specific time window (30 days). Customer Insights' Custom model (binary classification) is designed for exactly this scenario, allowing you to train a model on historical purchase data, web browsing behavior, and demographic data to predict a yes/no outcome. Product recommendation and conversion likelihood models are not available as built-in prediction types in Customer Insights, and churn prediction focuses on existing customers leaving, not new product adoption.

Answer

Product recommendation model

Answer

Customer churn model

Answer

Conversion likelihood model

Question 3

You are troubleshooting a Customer Insights unification process that fails to match records that you know belong to the same customer. Both sources contain a common email field, but many emails are in different formats (e.g., 'john.doe@contoso.com' vs 'jdoe@contoso.com'). What should you do?

Accepted Answer

Use fuzzy matching on email with normalization. Option D is correct because fuzzy matching with normalization allows Customer Insights to handle variations in email formats (e.g., 'john.doe@contoso.com' vs 'jdoe@contoso.com') by using similarity algorithms (like Levenshtein distance) and normalizing data (e.g., removing dots or case differences) to improve match accuracy. This directly addresses the mismatch caused by different email formats while still leveraging the email field for deduplication.

Answer

Remove the email condition from matching rules

Answer

Use exact match on email

Answer

Preprocess data to standardize email formats

Question 4

A data scientist reviews the custom prediction configuration shown. The prediction output includes a score between 0 and 1. What does a score of 0.9 indicate?

Accepted Answer

High likelihood of purchase within 30 days. In Dynamics 365 Customer Insights, the custom prediction model for purchase likelihood outputs a score between 0 and 1, where a higher score indicates a greater probability of the predicted event occurring. A score of 0.9 means the model predicts a 90% probability that the customer will make a purchase within the next 30 days, representing a high likelihood of purchase.

Answer

Low likelihood of purchase within 30 days

Answer

Model confidence in the prediction

Answer

Churn risk score

Question 5

A retail company uses Dynamics 365 Customer Insights - Data. They have multiple data sources: online transactions, loyalty program, and social media. They need to create a unified customer profile that resolves identities across these sources. Which process in Customer Insights should they configure to achieve this?

Accepted Answer

Data unification. Data unification in Dynamics 365 Customer Insights - Data is the process that matches and merges customer records from multiple data sources (online transactions, loyalty program, social media) into a single, unified customer profile. It resolves identity conflicts by using matching rules and deduplication to link records belonging to the same individual across disparate systems, enabling a 360-degree view of the customer.

Answer

Measures

Answer

Data transformation

Answer

Enrichment

Question 6

A company wants to use Dynamics 365 Customer Insights to generate AI-driven predictions about customer lifetime value. They have transactional data and customer demographics. Which feature should they use?

Accepted Answer

Predictive models. Predictive models in Dynamics 365 Customer Insights are specifically designed to generate AI-driven predictions, such as customer lifetime value (CLV), by analyzing historical transactional data and customer demographics. This feature uses machine learning algorithms to forecast future behavior, making it the correct choice for this scenario.

Answer

Segments

Answer

Enrichment

Answer

Measures

Question 7

A manufacturing company uses Dynamics 365 Sales and Customer Insights. They want to identify customers who are likely to churn based on support ticket volume and purchase recency. Which Customer Insights feature should they use to build this analysis?

Accepted Answer

Predictive models. A is correct because Predictive models in Dynamics 365 Customer Insights use built-in machine learning to analyze historical data—such as support ticket volume and purchase recency—and generate a churn probability score for each customer. This allows the company to proactively identify customers at risk of churning without requiring custom data science work.

Answer

Measures

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Segments

Answer

Enrichment

Question 8

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. Option B is correct because 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

Answer

Customers with a CLV of exactly 1000

Answer

Customers with a CLV less than 1000

Question 9

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

Accepted Answer

Predictive models for churn and purchase propensity. Option C is correct because 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

Answer

Lead scoring

Answer

Anomaly detection in transaction data

Question 10

A company uses Dynamics 365 Customer Insights - Data and wants to create a segment of high-value customers based on their total purchase amount in the last 90 days. The purchase data is in a separate table. What must they first create to build this segment?

Accepted Answer

A relationship. To build a segment in Dynamics 365 Customer Insights - Data that references data from a separate table (e.g., purchase transactions), you must first define a relationship between the customer entity and that table. A relationship establishes the key mapping (e.g., CustomerID) that allows the system to join the tables and evaluate conditions like total purchase amount across the two datasets.

Answer

An enrichment

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A measure

Answer

A new data source

Question 11

A marketing team at a manufacturing company uses Dynamics 365 Customer Insights to target customers with personalized offers. They notice that the same customer receives multiple identical emails because the system treats each interaction as a separate profile. Which configuration step should they prioritize to resolve this issue?

Accepted Answer

Configure match rules to merge duplicate customer profiles. Option B is correct because duplicate customer profiles cause the same person to receive multiple identical emails. Configuring match rules in Dynamics 365 Customer Insights allows the system to identify and merge duplicate profiles based on attributes like email or name, ensuring a single unified customer view and preventing redundant communications.

Answer

Create new measures to track email engagement

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Verify that all data sources are correctly connected

Answer

Add more enrichment data to improve profile completeness

Question 12

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

Answer

Create a dataflow to filter duplicates

Answer

Use Power Automate to remove duplicates

Question 13

A company uses Dynamics 365 Customer Insights - Journeys. Which THREE activities can be used in a journey? (Select THREE.)

Accepted Answer

Send push notification. Send push notification is a correct activity because Dynamics 365 Customer Insights - Journeys allows you to add push notification actions to a journey, enabling real-time engagement with customers via mobile apps. This leverages the customer's consent and device registration data to deliver targeted messages.

Answer

Update inventory

Answer

Generate invoice

Question 14

A marketing team uses Dynamics 365 Customer Insights - Journeys. They need to create a journey that sends a personalized email to contacts based on their purchase history stored in a Dynamics 365 Sales entity. Which TWO components must they configure to ensure the journey runs correctly? (Choose two.)

Accepted Answer

Trigger. A trigger is required to start the journey when a specific event occurs, such as a contact being added to a segment or a custom event. In this scenario, the trigger initiates the journey based on the purchase history data from the Dynamics 365 Sales entity, ensuring the journey runs for the right contacts at the right time.

Answer

Email message

Answer

Condition

Answer

Query

Question 15

A retail company wants to use Dynamics 365 Customer Insights to create a unified customer profile that combines data from their e-commerce platform, loyalty program, and in-store POS system. Which feature should they use to identify and merge duplicate customer records?

Accepted Answer

Match and merge. The 'Match and merge' feature in Dynamics 365 Customer Insights is specifically designed to identify duplicate customer records across different data sources (e-commerce, loyalty, POS) and unify them into a single, cohesive customer profile. It uses predefined or custom matching rules to detect duplicates based on attributes like email or phone number, then merges them while preserving the best data from each source.

Answer

Enrichment with external data

Answer

Data ingestion from various sources

Answer

Segmentation based on customer attributes

Question 16

A retail company uses Dynamics 365 Customer Insights - Data to unify customer data from multiple sources. After running the data unification process, they notice that some duplicate records were not merged. Which step in the data unification process should they review to adjust the matching rules?

Accepted Answer

Match. The Match step in Dynamics 365 Customer Insights - Data is where you define and configure matching rules (e.g., fuzzy matching, exact matching, or custom conditions) to identify duplicate records across unified data sources. If duplicates were not merged, the matching rules likely need adjustment—such as lowering the confidence threshold or adding additional fields—to improve duplicate detection. Reviewing the Match step allows you to refine these rules and ensure more accurate record unification.

Answer

Ingest

Answer

Merge

Answer

Enrich

Question 17

A marketing manager notices that the customer churn prediction model in Dynamics 365 Customer Insights is not updating with new data. What is the most likely cause?

Accepted Answer

The prediction model is not scheduled to refresh. In Dynamics 365 Customer Insights, prediction models are machine learning models that must be explicitly scheduled to refresh on a recurring basis. If the model is not scheduled to refresh, it will not automatically ingest new data, causing the churn predictions to become stale. Option D correctly identifies this as the most likely cause because the model's refresh schedule controls when it re-trains or updates with fresh data.

Answer

The segment is not refreshed

Answer

The measure is not calculated

Answer

The data source connection is lost

Question 18

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

Accepted Answer

Salesforce. Option A is correct because 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 19

A company wants to use Dynamics 365 Customer Insights to analyze customer purchase patterns over time. Which feature should they use to view trends and aggregate data?

Accepted Answer

Measures. Measures in Dynamics 365 Customer Insights are specifically designed to aggregate and summarize data, such as calculating total purchases, average order value, or frequency over time. This allows users to view trends and patterns in customer behavior by creating calculated metrics from raw data sources.

Answer

Enrichments

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Segments

Answer

Data sources

Question 20

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.

Answer

Enrichment with external data

Answer

Match rules for deduplication

Answer

Data source connections