Articles on futility stopping

What Can You Learn From Running an A/B Test for 2 Years?

AB Test Case Study

We just concluded an A/B test on Analytics-Toolkit.com that has been left to run for just over 2 years. And it failed, as in failing to demonstrate a statistically significant effect based on the significance threshold it was designed for. Has it been a waste of time, though, or can we actually learn something from […] Read more…

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Futility Stopping Rules in AGILE A/B Testing

Stopping for Lack of Effect (Futility)

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 […] Read more…

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Efficient AB Testing with the AGILE Statistical Method

AGILE AB Testing

Don’t we all want to run tests as quickly as possible, reaching results as conclusive and as certain as possible? Don’t we all want to minimize the number of users we send to an inferior variant and to implement a variant with positive lift as quickly as possible? Don’t we all want to get rid of […] Read more…

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