Bandit testing or Multi-Armed Bandits (MAB) is a testing methodology which uses algorithms that seek to optimise for your conversion goal during rather than after an experiment is completed. It does this by aggressively switching traffic to the highest converting variant as the test progresses with the aim to maximising the conversion rate.
This is especially suited to testing headlines and other content that has a very short lifespan (e.g. limited offer promotional content) and continuous, long-term testing. The chart below illustrates graphically how the bandit algorithm allows for a smooth transition of traffic from the exploration phase of testing to exploitation of the winning variant.
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