The free A/B testing platform, Google Optimize, is sunsetting and will no longer be available. What should experimenters do? This article outlines three simple steps to prepare for the sunset. Hint: don't just sit around and watch it!
How many visitors do I need to run a statistically significant A/B test and achieve valid, reliable results? This article will tell you everything you need to know to correctly calculate sample size and test duration for a split-test. Learn sample size best practices and industry-standard tools.
Calculating the Minimum Detectable Effect (MDE) can feel like a hair-pulling, speculative exercise. Luckily, this step-by-step guide is here to show you exactly how to accurately calculate your MDE to yield powerful, trustworthy test results.
Low sample testing is problematic and can result in hugely mis-leading data where tests appear to be enormous winners but, in actuality, aren't. This article presents a practical 5-step approach to overcome the traps of low sample testing and arrive at valid, trustworthy results. What are the 5-steps? Find out here.
Understanding and calculating statistical significance is quite complex. Many experimenters don’t truly know what statistical significance is or how to derive a statistically significant test result. To properly call a winning (or losing) A/B test, it’s really important to clearly understand what a statistically significant result is and means. This article, written in plain English is here to set it all straight for you.
It may seem like a small change, but optimizing your navigational menu can have a big impact on conversions. This article provides you with do's, don'ts, and the top-10 navigational bar A/B test ideas you absolutely must try to easily increase conversions on your site.
A/B testing your app delivers the best possible experience for users and validates your assumptions and ideas. In this comprehensive article, discover the benefits of app A/B testing, how to do it, and the optimal process to follow.
It's seems there's no good system for planning and prioritizing which A/B tests to run. Keeping track of which tests you've run, plan to run, or are currently running is an even bigger challenge. That is until now. Check out this short video to get an inside view into how Speero plans and prioritizes their tests. Then apply the insights to optimize your own test planning and prioritization process.
Calculating and verifying if your test has an SRM issue is key to obtaining trustworthy test results. This short article outlines the in's and out's of SRM, describes what it is, why you need to be looking at it when testing, and how to correct for it, if an SRM issue occurs.
