The concept of statistical significance is central to planning, executing and evaluating A/B (and multivariate) tests, but at the same time it is the most misunderstood and misused statistical tool in internet marketing, conversion optimization, landing page optimization, and user testing.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
What is the goal of A/B testing? How long should I run a test for? Is it better to run many quick tests, or one long one? How do I know when is a good time to stop testing? How do I choose the significance threshold for a test? Is there something special about 95%? Does it make sense to run tests at 50% significance? How about 5%? What is the cost of adding more variants to test?| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
This is a comprehensive guide to the different types of costs and benefits, risks and rewards related to A/B testing. Understanding them in detail should be valuable to A/B testers and businesses considering whether to engage in A/B testing or not, what to A/B test and what not to test, etc. As far as I am aware, this is the first attempt to systematically review all the different factors contributing to the return on investment from the process of A/B testing. Here I will cover A/B testing m...| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...
A central feature of sequential testing is the idea of stopping “early”, as in “earlier compared to an equivalent fixed-sample size test”. This allows running A/B tests with fewer users and in a shorter amount of time while adhering to the targeted error guarantees.| Blog for Web Analytics, Statistics and Data-Driven Internet Marketing | Analy...