This framework is a guiding tool on when to run a multi-armed bandit vs. running a true A/B test. The general benefits are that A/B testing allows for a more statistically controlled learning environment, while MAB is more focused on generating a win as quickly as possible (at the sacrifice of understanding 'why')
Generally, this comes up when A/B testing may not have enough time to run (or traffic volume). Or, there is a seasonal campaign that is a one-off (with the above parameters) - so use this framework to help guide in the decision making process for when to MAB vs. run an A/B/n test
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