- A
Export all data to Azure Machine Learning and build a custom churn prediction model, then import the results back into Customer Insights.
Why wrong: Incorrect: This is unnecessarily complex; Customer Insights already has a churn model.
- B
Use Dynamics 365 Customer Insights to export the data to Power BI, visualize churn patterns, and manually identify likely churners.
Why wrong: Incorrect: This requires manual analysis and does not leverage AI.
- C
Use the built-in Churn Prediction model in Dynamics 365 Customer Insights to analyze the data and get churn scores for each customer.
Correct: The AI model is prebuilt and designed for this purpose.
- D
Create a manual segmentation rule in Customer Insights based on customers with no purchases in the last 30 days.
Why wrong: Incorrect: This does not use predictive AI.
MB-910 Describe Dynamics 365 Customer Insights Practice Question
This MB-910 practice question tests your understanding of describe dynamics 365 customer insights. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are a data analyst for a financial services company that uses Dynamics 365 Customer Insights. Your organization wants to use the Customer Insights data to improve customer retention. You have access to transaction data, customer service call logs, and web browsing behavior data. You need to identify customers who are likely to churn in the next 30 days. The solution must use built-in AI capabilities. What should you do?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use the built-in Churn Prediction model in Dynamics 365 Customer Insights to analyze the data and get churn scores for each customer.
Option C is correct because Dynamics 365 Customer Insights includes a built-in AI-powered Churn Prediction model that analyzes transaction data, customer service logs, and web browsing behavior to generate churn scores for each customer. This model uses pre-trained machine learning algorithms specifically designed for customer retention scenarios, requiring no custom development or external tools. It directly meets the requirement to use built-in AI capabilities without manual intervention or export to other services.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Export all data to Azure Machine Learning and build a custom churn prediction model, then import the results back into Customer Insights.
Why it's wrong here
Incorrect: This is unnecessarily complex; Customer Insights already has a churn model.
- ✗
Use Dynamics 365 Customer Insights to export the data to Power BI, visualize churn patterns, and manually identify likely churners.
Why it's wrong here
Incorrect: This requires manual analysis and does not leverage AI.
- ✓
Use the built-in Churn Prediction model in Dynamics 365 Customer Insights to analyze the data and get churn scores for each customer.
Why this is correct
Correct: The AI model is prebuilt and designed for this purpose.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a manual segmentation rule in Customer Insights based on customers with no purchases in the last 30 days.
Why it's wrong here
Incorrect: This does not use predictive AI.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse a simple rule-based segmentation (Option D) with AI-driven prediction, or assume that any external tool like Azure Machine Learning or Power BI is required for advanced analytics, when the exam specifically tests knowledge of Customer Insights' out-of-the-box AI models.
Detailed technical explanation
How to think about this question
The Churn Prediction model in Customer Insights uses a gradient-boosted decision tree algorithm trained on historical customer data to predict the probability of churn within a specified time window (e.g., 30 days). It automatically selects the most predictive features from the ingested data, such as recency of purchase, call frequency, and browsing session duration, and outputs a churn score between 0 and 1. In a real-world scenario, a financial services company could use these scores to trigger automated retention campaigns, such as sending personalized offers to customers with scores above 0.7, without any data scientist involvement.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MB-910 question test?
Describe Dynamics 365 Customer Insights — This question tests Describe Dynamics 365 Customer Insights — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the built-in Churn Prediction model in Dynamics 365 Customer Insights to analyze the data and get churn scores for each customer. — Option C is correct because Dynamics 365 Customer Insights includes a built-in AI-powered Churn Prediction model that analyzes transaction data, customer service logs, and web browsing behavior to generate churn scores for each customer. This model uses pre-trained machine learning algorithms specifically designed for customer retention scenarios, requiring no custom development or external tools. It directly meets the requirement to use built-in AI capabilities without manual intervention or export to other services.
What should I do if I get this MB-910 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 24, 2026
This MB-910 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MB-910 exam.
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