MB-910 Describe Dynamics 365 Sales Practice Question
Your organization uses Dynamics 365 Sales and wants to use AI to score leads based on their likelihood to convert. The sales team reports that many high-scored leads are not contacting them. How should you adjust the lead scoring model?
⚠ Common exam trap
Many candidates think increasing the weight of an existing attribute (like lead source) is the fix, but the real issue is the lack of behavioral attributes that directly measure lead engagement, which the AI model needs to differentiate between passive and active leads.
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 attributes such as email open rates and website visits
Adding behavioral attributes like email open rates and website visits provides richer engagement signals to the AI model, which can better predict conversion intent. In Dynamics 365 Sales, the predictive lead scoring model uses machine learning to analyze historical lead data, and incorporating these interaction-based attributes helps the model distinguish between leads that are merely high-scored due to demographic or firmographic data and those showing active interest. This adjustment directly addresses the issue of high-scored leads not contacting the sales team by aligning the score with actual engagement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Manually override scores for leads that seem promising
Why it's wrong here
Manual overrides defeat the purpose of an AI model.
- ✗
Reduce the number of leads fed into the model
Why it's wrong here
Reducing leads does not improve scoring accuracy.
- ✓
Add attributes such as email open rates and website visits
Why this is correct
Engagement attributes improve predictive accuracy.
- ✗
Increase the weight of lead source from administrative events
Why it's wrong here
Administrative events are often less indicative of interest.
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