AI Associate Data for AI Practice Question
A company wants to use Einstein Prediction Builder to predict customer churn. Which data preparation step is essential before building the model?
⚠ Common exam trap
Salesforce often tests the misconception that data must come from Data Cloud or that you need to pre-create storage objects, when in fact the core prerequisite is simply defining the prediction objective and target date field.
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
✓
Define the prediction objective and the target date field.
Einstein Prediction Builder requires you to define the prediction objective (e.g., 'Will this customer churn?') and specify the target date field that marks the event. This step is essential as it tells the model what to predict and over what time window, enabling the automated feature engineering and model training process.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ensure the data is in a Salesforce connected data source like Data Cloud.
Why it's wrong here
Einstein Prediction Builder can use data directly from Salesforce objects.
- ✓
Define the prediction objective and the target date field.
Why this is correct
The prediction objective (e.g., churn) is required to train the model.
- ✗
Create a formula field to calculate the churn probability.
Why it's wrong here
Formula fields are not used; the model calculates probabilities.
- ✗
Create a new custom object to store the prediction results.
Why it's wrong here
Prediction results are stored automatically; no custom object is needed.
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