MB-910 Describe Dynamics 365 Customer Insights Practice Question
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?
⚠ Common exam trap
Many candidates confuse the generic term 'conversion likelihood' with a built-in model type, but Microsoft specifically tests that only 'Custom model (binary classification)' is available for such predictive tasks in Customer Insights, and that product recommendation and churn models serve different purposes.
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
✓
Custom model (binary classification)
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 analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Product recommendation model
Why it's wrong here
Recommendations suggest products, not purchase likelihood.
- ✗
Customer churn model
Why it's wrong here
Churn predicts disengagement.
- ✓
Custom model (binary classification)
Why this is correct
Custom models predict specific outcomes.
- ✗
Conversion likelihood model
Why it's wrong here
Conversion models are for specific events like subscription.
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