Changing Running Experiments Safely and Flexibly in GrowthBook

In GrowthBook 2.7, making changes to running experiments has become safer and more flexible, thanks to guided flows and sticky bucketing, which help avoid bias and preserve user experience. When decreasing traffic to an experiment, users have options to either start a new phase, apply changes to everyone, or apply changes only to new traffic, with sticky bucketing enabling the latter to maintain data integrity and avoid bias. Increasing traffic is less complex and can be done without starting a new phase, by adjusting targeting or traffic percentages. Restarting experiments may be necessary due to bugs or design changes, and GrowthBook provides comprehensive guidance to ensure informed decision-making, as well as detailed documentation on sticky bucketing and experiment modifications.

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