MB-910 Describe Dynamics 365 Customer Insights Practice Question
Contoso Ltd. is a multinational retailer using Dynamics 365 Customer Insights to unify customer data from three regional CRM systems (North America, Europe, Asia) and a global e-commerce platform. The company has configured data sources for each system and run data unification, but the unified customer profiles show a high number of duplicates (approximately 15% of profiles are duplicates). The administrator has tried increasing the match confidence threshold but the problem persists. Additionally, the company wants to ensure that customer consent preferences (opt-in for marketing) are synchronized across all profiles. The administrator is considering adjusting the unification rules. The current matching rules use only email address. What is the best course of action to reduce duplicates while maintaining data accuracy?
⚠ Common exam trap
Test-takers frequently think lowering the confidence threshold will reduce duplicates, but in reality, lowering the threshold increases the number of matched records (including false positives), while the correct approach is to add more matching conditions to improve precision without sacrificing recall.
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
✓
Add additional matching conditions such as phone number and postal code
Adding additional matching conditions (such as phone number and postal code) increases the precision of duplicate detection. With only email as the match condition, records that share the same email but belong to different individuals (e.g., family accounts) or have data entry errors are incorrectly merged. By requiring multiple identifiers to match, the system reduces false positives while still catching true duplicates, improving the overall accuracy of the unified customer profiles.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create separate unifications for each region
Why it's wrong here
This would not solve cross-region duplicates.
- ✓
Add additional matching conditions such as phone number and postal code
Why this is correct
Multiple conditions improve matching accuracy.
- ✗
Remove the email condition and use only customer name
Why it's wrong here
Name alone is less reliable.
- ✗
Lower the match confidence threshold to 50% to match more records
Why it's wrong here
Lowering threshold may increase false positives.
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Written by Johnson Ajibi, MSc IT Security
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