AI Associate Salesforce Einstein AI Features Practice Question
A data scientist wants to use Einstein Discovery to analyze customer churn. They want to understand which factors contribute most to churn and get actionable suggestions. Which THREE outputs does Einstein Discovery provide?
⚠ Common exam trap
Watch out — candidates often confuse Einstein Discovery's outputs (key drivers, story, improvement suggestions) with Einstein Prediction Builder's outputs (prediction scores and probability distributions), leading them to select Option A incorrectly.
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
✓
Improvement suggestions (recommended actions)
Einstein Discovery provides improvement suggestions (recommended actions) that guide data scientists on specific changes to reduce churn. These actionable insights are generated from the predictive model's analysis of historical data, offering concrete steps like 'increase engagement frequency' or 'offer discount' to improve outcomes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Prediction score for each record
Why it's wrong here
Prediction scores are from Prediction Builder, not Discovery.
- ✓
Improvement suggestions (recommended actions)
Why this is correct
Suggestions provide actionable steps to improve the outcome.
- ✓
Story (narrative explanation of insights)
Why this is correct
Stories summarize key findings in plain language.
- ✓
Key drivers (most influential factors)
Why this is correct
Key drivers show which variables most affect the outcome.
- ✗
Waterfall chart (visualization of step-by-step impact)
Why it's wrong here
Waterfall charts are available but not one of the three main outputs listed.
Visual reference
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This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.