Multi-Armed Bandit

In marketing terms, a multi-armed bandit solution is a ‘smarter’ or more complex version of A/B testing that uses machine learning algorithms to dynamically allocate traffic to variations that are performing well, while allocating less traffic to variations that are underperforming. In theory, multi-armed bandits should produce faster results since there is no need to wait for a single winning variation.


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