AI Associate AI Fundamentals Practice Question
A company wants to deploy an Einstein Prediction Builder model to predict lead conversion within 30 days. They have historical data from the past 12 months. Which data preprocessing step is most critical to ensure the model learns correctly?
⚠ Common exam trap
Salesforce often tests the concept of 'target variable definition' in time-series or prediction scenarios, where candidates mistakenly focus on data cleaning or feature engineering instead of the precise labeling of the outcome variable, which is the foundational step for supervised learning.
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
✓
Ensure the target variable is computed based on conversion status at exactly 30 days from creation.
The target variable for a time-based prediction model like Einstein Prediction Builder must be computed at a precise, consistent point in time—in this case, exactly 30 days from lead creation. If the target is computed at varying intervals, the model will learn incorrect patterns, as it cannot distinguish between leads that converted at 31 days versus those that never converted, leading to biased or invalid predictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Normalize all numerical features to a 0-1 range.
Why it's wrong here
Normalization not required for tree-based models.
- ✗
Remove leads that converted after 30 days.
Why it's wrong here
Leads converting after 30 days are valid negative examples.
- ✗
Include only leads that were assigned to a sales rep.
Why it's wrong here
Excluding unassigned leads may bias the model.
- ✓
Ensure the target variable is computed based on conversion status at exactly 30 days from creation.
Why this is correct
Accurate target alignment is crucial.
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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.