What is evaluation difference between offline and online recommendation metrics?
Updated May 16, 2026
Short answer
Offline metrics evaluate models on historical data, online metrics evaluate real user behavior.
Deep explanation
Offline evaluation uses metrics like precision, recall, and NDCG on test datasets. Online evaluation uses A/B testing, click-through rate (CTR), and conversion rates in live systems.
Real-world example
A/B testing Netflix recommendation changes on live users.
Common mistakes
- Relying only on offline metrics.
Follow-up questions
- Why offline metrics can mislead?
- What is A/B testing?