Most, if not all successful online businesses nowadays rely on one or more systems for conducting A/B tests in order to inform business decisions ranging from simple website or advertising campaign interventions to complex product and business model changes. While testing might have become a prerequisite for releasing the tiniest of changes, one type of […] Read more…
I’m happy to announce the release of two long-awaited features for our A/B Testing Calculator: Support for non-binomial metrics like average revenue per user A new custom API for sending experiment data to the calculator Below is an explanation of each of these new features in some detail. Support for Non-Binomial Data While our more […] Read more…
The long wait is finally over! “Statistical Methods in Online A/B Testing” can now be found as a paperback and an e-book on your preferred Amazon store. The book is a comprehensive guide to statistics in online controlled experiments, a.k.a. A/B tests, and tackles the difficult matter of statistical inference in a way accessible to […] Read more…
The question “How to test if my website has a small number of users” comes up frequently when I chat to people about statistics in A/B testing, online and offline alike. There are different opinions on the topic ranging from altering the significance threshold, statistical power or the minimum effect of interest all the way […] Read more…
We are happy to present a brand new addition to our website: a comprehensive A/B testing glossary containing terms and abbreviations used testing as part of conversion rate optimization (CRO). Definitions start from very basic things such as “A/B test“, “mean“, “conversion rate” and “revenue per user“, go through “hypothesis“, “null hypothesis“, “standard deviation“, “p-value” […] Read more…
The secluded and isolated deserted island setting has been used as the stage for many hypothetical explanations in economics and philosophy with the scarcity of things that can be developed as resources being a central feature. Scarcity and the need to keep risk low while aiming to improve one’s situation is what make it a […] Read more…
I’ve already done a detailed breakdown of costs & benefits in A/B testing as well as the risks and rewards and how A/B testing is essentially a risk management solution. In this short installment I’d like to focus on the trade-off between limiting the downside and restricting the upside which is present in all risk management […] Read more…
I see a nice trend in recent discussions on A/B testing: more and more people realize the need for proper statistical design and analysis which is a topic I hold dear as I’ve written dozens of articles and a few white-papers on. However, there are cases in which statistical validity is discussed without consideration for […] Read more…
The process of A/B testing (a.k.a. online controlled experiments) is well-established in conversion rate optimization for all kinds of online properties and is widely used by e-commerce websites. On this blog I have already written in depth about the statistics involved as well as the ROI calculations in terms of balancing risk and reward for […] Read more…
Oct 2022 update: A newer, much larger and likely less biased meta analysis of 1,001 tests is now available! What can you learn from 115 publicly available A/B tests? Usually, not much, since in most cases you would be looking at case studies with very basic data about what was tested and the outcome of […] Read more…
In many controlled experiments, including online controlled experiments (a.k.a. A/B tests) the result of interest and hence the inference made is about the relative difference between the control and treatment group. In A/B testing as part of conversion rate optimization and in marketing experiments in general we use the term “percent lift” (“percentage lift”) while in […] Read more…
The problem most-often faced by owners of websites who want to take a scientific approach to improving them by using A/B testing is that they might have relatively small revenue. Thus, when the ROI calculation for the A/B test is done it might turn out that it is economically unfeasible to test. In some cases, […] 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.