The correct answer is to enable the churn prediction model in the AI insights module. This is the right configuration because Dynamics 365 Customer Insights includes prebuilt AI models that analyze customer data—such as interactions, transactions, and engagement history—to predict which customers are likely to churn within a specified time frame, like 30 days. The model uses machine learning to identify behavioral patterns and assign a churn score, allowing the financial services company to proactively target at-risk customers with retention campaigns. On the MB-910 exam, this question tests your understanding of the AI insights module’s capabilities within Customer Insights, often appearing as a scenario where you must distinguish between prebuilt AI models and custom analytics features. A common trap is confusing the churn model with the product recommendation model, which serves a different purpose. Memory tip: think “Churn = Customer Health,” and remember that enabling the prebuilt model in AI insights is the only way to get that predictive score without custom development.
MB-910 Describe Dynamics 365 Customer Insights Practice Question
This MB-910 practice question tests your understanding of describe dynamics 365 customer insights. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A financial services company uses Dynamics 365 Customer Insights to generate a 360-degree view of customers. They want to use AI to predict which customers are likely to churn in the next 30 days. What should they configure?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable the churn prediction model in the AI insights module
The churn prediction model in the AI insights module is the correct configuration because Dynamics 365 Customer Insights provides prebuilt AI models, including a churn prediction model, that analyze customer data (e.g., interactions, transactions, and engagement) to predict which customers are likely to churn within a specified time frame, such as 30 days. This model uses machine learning to identify patterns and assign a churn score, enabling proactive retention efforts.
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.
✓
Enable the churn prediction model in the AI insights module
Why this is correct
The AI insights module includes prebuilt models for churn prediction.
Related concept
Read the scenario before looking for a memorised answer.
✗
Define a measure to calculate average transaction amount
Why it's wrong here
Measures calculate historical metrics, not predictions.
✗
Create a static segment based on past churn behavior
Why it's wrong here
Segments are not predictive; they group existing data.
✗
Add enrichment data from external demographics
Why it's wrong here
Enrichment adds data but does not predict future behavior.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse static segmentation or manual measures with AI-powered predictive models, assuming that historical data alone can predict future behavior without machine learning.
Detailed technical explanation
How to think about this question
The churn prediction model in Customer Insights uses a binary classification algorithm trained on historical customer data, including features like recency, frequency, and monetary value (RFM), as well as engagement metrics. The model outputs a churn probability score for each customer, which can be used to create dynamic segments for targeted campaigns. In a real-world scenario, a financial services company might combine this with a retention campaign to offer personalized incentives to high-risk customers, reducing churn rates by up to 20%.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
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: Enable the churn prediction model in the AI insights module — The churn prediction model in the AI insights module is the correct configuration because Dynamics 365 Customer Insights provides prebuilt AI models, including a churn prediction model, that analyze customer data (e.g., interactions, transactions, and engagement) to predict which customers are likely to churn within a specified time frame, such as 30 days. This model uses machine learning to identify patterns and assign a churn score, enabling proactive retention efforts.
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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These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. 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?
medium
✓ A.Predictive models
B.Measures
C.Segments
D.Enrichment
Why A: 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.
Last reviewed: Jun 24, 2026
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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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