In this article we continue our examination of the AGILE statistical approach to AB testing with a more in-depth look into futility stopping, or stopping early for lack of positive effect (lack of superiority). We’ll cover why such rules are helpful and how they help boost the ROI of A/B testing, why a rigorous statistical rule is required in order to stop early when results are unpromising or negative and how it works in practice. We’re reviewing this from the standpoint of the AGILE me...| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
Running shorter tests is key to improving the efficiency of experimentation as it translates to smaller direct losses from testing inferior experiences and also less unrealized revenue due to late implementation of superior ones.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...