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AI Associate AI Fundamentals Practice Question

A data scientist notices that an Einstein Discovery model predicts a low probability of conversion for all leads in a new campaign, even though the campaign targets high-value accounts. Which initial diagnostic step should be taken?

⚠ Common exam trap

Salesforce often tests the misconception that retraining is the immediate fix for poor model performance, but the trap here is that candidates overlook the fundamental diagnostic step of checking for data drift before taking any corrective action.

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

Compare the feature distributions of the training and campaign data

The most likely cause of a model predicting low conversion for all leads in a new campaign is a shift in feature distributions between the training data and the campaign data (covariate shift). Checking these distributions is the standard initial diagnostic step to identify if the model is encountering data it was not trained on, which would invalidate its predictions. This aligns with best practices for model monitoring and data validation in Einstein Discovery.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Retrain the model with the new campaign data included

    Why it's wrong here

    Retraining without understanding may mask the issue. First diagnose.

  • Check the Einstein model recipe for incorrect filters

    Why it's wrong here

    Filters in recipe could cause mismatches, but data distribution check is more fundamental.

  • Compare the feature distributions of the training and campaign data

    Why this is correct

    Distribution mismatch often explains low predictions; if features differ, the model may not apply.

  • Increase the prediction confidence threshold

    Why it's wrong here

    Threshold change does not fix predictions; it only adjusts output labeling.

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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.