AI Associate AI Capabilities in CRM Practice Question
A Salesforce admin has enabled Einstein Opportunity Scoring but notices that some opportunities are not being scored. The admin checks the data and finds that the opportunities have all required fields. What could be another reason for missing scores?
⚠ Common exam trap
Watch out — candidates often assume missing scores are always due to missing fields or permissions, but Salesforce specifically requires a minimum data volume (100 opportunities with activities) for Einstein models to function.
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 org has fewer than 100 opportunities with activities
Einstein Opportunity Scoring requires a minimum of 100 opportunities with activities (e.g., emails, events, tasks) in the last 90 days to generate scores. Even if all required fields are present, the model needs sufficient historical data to calculate a predictive score. Option C correctly identifies this data volume threshold as the likely cause.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Opportunity team members have not been assigned
Why it's wrong here
Team members are not related to scoring.
- ✗
The org is on a Professional Edition
Why it's wrong here
Einstein Opportunity Scoring is available in Professional, Enterprise, and Unlimited.
- ✓
The org has fewer than 100 opportunities with activities
Why this is correct
Einstein requires sufficient data history to generate scores.
- ✗
The opportunities are missing custom fields
Why it's wrong here
Custom fields are not required for scoring.
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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.