AI Associate Salesforce Einstein AI Features Practice Question
A marketing team wants to identify which leads are most likely to convert, based on historical lead data. They need a score from 1-99 visible on lead records. Which feature should they implement?
⚠ Common exam trap
Candidates often confuse Einstein Lead Scoring with Einstein Prediction Builder, thinking the latter can be used for lead scoring, but Prediction Builder requires custom configuration and does not provide the out-of-the-box 1-99 score on lead records.
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
✓
Einstein Lead Scoring
Einstein Lead Scoring is the correct feature because it is specifically designed to assign a score from 1 to 99 to leads based on historical conversion data and predictive models. This score is automatically calculated and displayed on lead records, enabling the marketing team to prioritize leads most likely to convert.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Einstein Prediction Builder
Why it's wrong here
Prediction Builder can create custom models, but Lead Scoring is the standard feature designed for this exact need.
- ✓
Einstein Lead Scoring
Why this is correct
This feature scores leads 1-99 based on conversion likelihood and displays on lead records.
- ✗
Einstein Opportunity Scoring
Why it's wrong here
Opportunity Scoring is for opportunities, not leads.
- ✗
Einstein Discovery
Why it's wrong here
Discovery provides analysis but does not produce lead scores.
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