seniorRecommendation Systems
What is A/B testing in recommendation systems?
Updated May 16, 2026
Short answer
A/B testing compares two recommendation models in production.
Deep explanation
Users are randomly split into control and treatment groups. One group sees the existing recommender, the other sees the new model. Metrics like CTR, conversion rate, and retention are compared to evaluate improvement.
Real-world example
Netflix testing new homepage ranking algorithm.
Common mistakes
- Not ensuring random assignment.
Follow-up questions
- What is statistical significance?
- What is guardrail metric?