Debug a model that does worse online than offline

A model scored well in offline evaluation, but after launch its online metrics are worse. How do you find out why? Walk through the likely causes (training-serving skew in features, data drift, leakage in the offline set, a mismatch between offline and online metrics, feedback loops), how you would check each one, and what you would change so it does not happen again.