MB-910 Describe Dynamics 365 Customer Insights Practice Question
A company wants to use AI to calculate the likelihood that a customer will churn. Which Customer Insights feature should they use?
⚠ Common exam trap
Watch out — candidates often confuse 'Segmentation' (which can include dynamic rules like 'last purchase > 90 days') with true predictive analytics, but segmentation only reflects past behavior, not a machine-learned probability of future churn.
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
✓
Predictive models
Predictive models in Dynamics 365 Customer Insights use machine learning to analyze historical customer data and calculate the likelihood of future outcomes, such as churn. This feature specifically builds a binary classification model that outputs a churn probability score for each customer, enabling proactive retention efforts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Predictive models
Why this is correct
Predictive models can forecast churn probability.
- ✗
Measures
Why it's wrong here
Measures are aggregations, not predictions.
- ✗
Segmentation
Why it's wrong here
Segments don't predict churn.
- ✗
Enrichment
Why it's wrong here
Enrichment adds data, not predictions.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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