Quick Answer
The answer is binary classification. This is the correct choice because Einstein Prediction Builder is specifically designed to predict binary outcomes—situations with only two possible results, such as whether a customer will churn (yes) or not churn (no) within the next 30 days. The builder trains a model on historical data to assign each customer a probability of belonging to one of these two labels, making it a perfect fit for churn prediction. On the Salesforce AI Associate exam, this question tests your understanding of when to use binary classification versus numeric or multi-category predictions; a common trap is confusing churn prediction with a regression task (like predicting churn date) or a multi-class problem (like predicting churn reason). Remember the key distinction: if the outcome is a clear yes/no, it’s binary. A handy memory tip is to think of binary as “two choices, like a coin flip”—heads for churn, tails for no churn.
This AI Associate practice question tests your understanding of ai capabilities in crm. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to use Einstein to predict which customers are likely to churn in the next 30 days. Which type of prediction should be created in Einstein Prediction Builder?
Numeric prediction
Why wrong: Numeric predicts a number, not a yes/no outcome.
Multi-class classification
Why wrong: Multi-class predicts more than two categories, not suitable for churn.
Regression
Why wrong: Regression is not a supported Einstein Prediction Builder type.
Binary classification
Binary classification predicts one of two outcomes, like churn or not churn.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Binary classification
Einstein Prediction Builder is designed for binary outcomes, such as whether a customer will churn (yes/no) within a specified time frame. A binary classification model predicts one of two possible labels, making it the correct choice for this churn prediction use case.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Numeric prediction
Why it's wrong here
Numeric predicts a number, not a yes/no outcome.
Multi-class classification
Why it's wrong here
Multi-class predicts more than two categories, not suitable for churn.
Regression
Why it's wrong here
Regression is not a supported Einstein Prediction Builder type.
Binary classification
Why this is correct
Binary classification predicts one of two outcomes, like churn or not churn.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Salesforce often tests the distinction between regression (numeric prediction) and classification (categorical prediction), and candidates mistakenly choose 'Numeric prediction' or 'Regression' because churn prediction involves a time-based numeric threshold (30 days), but the output is still a binary label, not a number.
Detailed technical explanation
Binary classification in Einstein Prediction Builder uses a logistic regression model under the hood, which outputs a probability score between 0 and 1. A threshold (default 0.5) is applied to assign the prediction to one of two classes. In real-world scenarios, the model can be tuned by adjusting the threshold to balance precision and recall based on business costs of false positives vs. false negatives.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
AI Capabilities in CRM — study guide chapter
Learn the concepts, then practise the questions
AI Capabilities in CRM practice questions
Targeted practice on this topic area only
All AI Associate questions
506 questions across all exam domains
Salesforce AI Associate AI Associate study guide
Full concept coverage aligned to exam objectives
AI Associate practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise AI Associate questions linked to AI Fundamentals.
Practise AI Associate questions linked to AI Capabilities in CRM.
Practise AI Associate questions linked to Ethical Considerations of AI.
Practise AI Associate questions linked to Data for AI.
Practise AI Associate questions linked to AI Associate fundamentals.
Practise AI Associate questions linked to AI Associate scenario.
Practise AI Associate questions linked to AI Associate troubleshooting.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
AI Capabilities in CRM — This question tests AI Capabilities in CRM — Read the scenario before looking for a memorised answer..
The correct answer is: Binary classification — Einstein Prediction Builder is designed for binary outcomes, such as whether a customer will churn (yes/no) within a specified time frame. A binary classification model predicts one of two possible labels, making it the correct choice for this churn prediction use case.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 30, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.