AI Associate AI Fundamentals Practice Question
A company wants to use Einstein Prediction Builder to predict customer churn. They have a dataset with 10,000 records and 50 features. What is the primary consideration for model accuracy?
⚠ Common exam trap
Salesforce often tests the misconception that dataset size is the primary driver of accuracy, but the trap here is that class balance is more critical than raw record count for classification models in Einstein Prediction Builder.
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
✓
The dataset must be balanced between churned and non-churned customers.
Einstein Prediction Builder uses automated machine learning (AutoML) to train models, and class imbalance is a critical factor that directly impacts model accuracy. If the dataset is highly skewed (e.g., 95% non-churned, 5% churned), the model may achieve high accuracy by simply predicting the majority class, but it will fail to identify actual churners. Einstein Prediction Builder includes built-in handling for imbalanced data, but the user must ensure the dataset is reasonably balanced or use techniques like oversampling to improve predictive performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The dataset size is too small for reliable predictions.
Why it's wrong here
10k records is sufficient if balanced.
- ✗
All features must be numerical and normalized.
Why it's wrong here
Prediction Builder handles categorical features.
- ✓
The dataset must be balanced between churned and non-churned customers.
Why this is correct
Balancing prevents bias towards majority class.
- ✗
The model needs to be retrained daily.
Why it's wrong here
Retraining frequency depends on data stability.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AI Associate question from scratch — 753 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.