AI Associate AI Fundamentals Practice Question
A company deploys Einstein Recommendation Builder on its e-commerce site. The recommendations are not personalized. What is the most likely cause?
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 model has not been trained with enough user behavior data.
Einstein Recommendation Builder relies on user interaction data to personalize. If insufficient data exists, recommendations become generic. Option A is correct. Option B is wrong because real-time sync is not required. Option C is wrong because the builder can work without a data scientist. Option D is wrong because the model can recommend products beyond categories.
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 model has not been trained with enough user behavior data.
Why this is correct
Personalization requires sufficient historical data.
- ✗
The company did not hire a data scientist to tune the model.
Why it's wrong here
Einstein Recommendation Builder is designed for business users.
- ✗
The recommendation engine is not syncing in real-time with the website.
Why it's wrong here
Real-time sync is not necessary for basic personalization.
- ✗
The product catalog is too large for the model to process.
Why it's wrong here
The model can handle large catalogs.
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