MB-910 Describe Dynamics 365 Customer Insights Practice Question
You are a data analyst for a financial services company that uses Dynamics 365 Customer Insights. The company has unified customer profiles and wants to use AI to predict which customers are likely to respond to a new credit card offer. They have historical data on previous offers, customer demographics, and transaction history. You have been asked to create a predictive model. After configuring the model, you notice that the model's accuracy is very low. You suspect that the data used for training is not representative. What is the most likely cause?
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
✓
The historical data has a low response rate, creating class imbalance.
The historical data may not include enough examples of customers who responded, leading to imbalanced data. Option B is wrong because missing data can be handled, but imbalance is more critical. Option C is wrong because the model can handle different time periods. Option D is wrong because the data source configuration is probably correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The historical data has a low response rate, creating class imbalance.
Why this is correct
Imbalanced data reduces model accuracy.
- ✗
The data unification process merged records incorrectly.
Why it's wrong here
Not indicated by low accuracy.
- ✗
The training data includes data from too many time periods.
Why it's wrong here
Not typically a problem.
- ✗
The data source connection to the transactional system is failing.
Why it's wrong here
Would cause missing data, not low accuracy.
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