Your question is When to Use Bandits. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You work on a growth team testing multiple onboarding variants in a consumer fintech app. A stakeholder suggests using a multi-armed bandit instead of a standard A/B/n test so traffic can shift faster toward better-performing variants, but you are concerned about whether that is the right choice for learning and decision-making.
How would you decide whether a multi-armed bandit approach makes sense for this growth experiment? What factors would make you prefer a bandit versus a fixed-horizon A/B/n test?