Contextual bandits FAQ
Use contextual bandits with Optimizely to maximize your conversions by delivering variations that are personalized by user based on the primary metric performance in combination with user attributes. While multi-armed bandits (MABs)multi-armed bandits (MABs) look for the single best-performing variation for all users, contextual bandits pick a winning variation for each user based on their contextual profile and impact on the primary metricprimary metric.
The benefits include the following:
- Provides the most personalized experience for every user.
- Increases the chances of conversions on the primary metric.
- Adapts to changes in visitor behavior, dynamically serving the best variation in every session.
Like MABs, contextual bandits optimize toward the primary metric but also account for user attributes in that optimization. They do not have sticky bucketing like A/B tests. See Experimentation distribution modesExperimentation distribution modes for information on Optimizely's automated distribution modes and use cases.