You work on a digital subscription product and are testing several onboarding variants intended to improve activation. A teammate suggests replacing a standard fixed-horizon A/B test with a multi-armed bandit so traffic can shift toward better-performing variants during the experiment.
What is a multi-armed bandit, and when would you use one for growth experiments instead of a standard A/B test? How would you decide whether it is appropriate for this onboarding test?