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. Despite this, many practitioners are yet to start conducting tests at the frontier of efficiency. This article presents ways to shorten […] Read more…
How long does a typical A/B test run for? What percentage of A/B tests result in a ‘winner’? What is the average lift achieved in online controlled experiments? How good are top conversion rate optimization specialists at coming up with impactful interventions for websites and mobile apps? This meta-analysis of 1,001 A/B tests analyzed using […] Read more…
I got a question today about our AGILE A/B testing calculator and the statistics behind it and realized that I’m yet to write a dedicated post explaining the efficiency gains from using the method in more detail. This despite the fact that these speed gains are clearly communicated and verified through simulation results presented in our AGILE […] Read more…
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%? […] Read more…
Take your A/B testing program to the next level
Want to take your A/B tests to the next level?
If you enjoyed this article and want to read more great content like it make sure to check out the book “Statistical Methods in Online A/B Testing” by the author, Georgi Georgiev, and take your experimentation program to the next level.