Introducing Multi-Armed Bandits in GrowthBook

GrowthBook has released beta bandits as part of its 3.3 update for Pro and Enterprise customers, allowing users to test multiple variations against each other while driving traffic towards better-performing arms. Bandits are particularly useful in short-term promotional campaigns or when testing multiple call-to-action designs, but they require a clear decision metric that is relatively stable and may not be ideal for learning about user behavior on several metrics. GrowthBook's bandits use Thompson Sampling to balance exploration and exploitation while preserving user experience through Sticky Bucketing, which ensures consistent user experiences across sessions. The platform accommodates changing user behavior by adjusting weights to prevent biased results, and it integrates with popular data warehouse solutions such as BigQuery, Snowflake, and Databricks. GrowthBook's bandits can adaptively allocate traffic within hours or less if events land in the data warehouse quickly. Users can get started with Bandits for free or check out the setup guide for more information. The platform is designed to live on top of existing data infrastructure without complicating it.

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