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Affordable A/B Tests: Google Optimize & AGILE A/B Testing

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

The Google Optimize Statistical Engine and Approach

Google Optimize is the latest attempt from Google to deliver an A/B testing product. Previously we had “Google Website Optimizer”, then we had “Content Experiments” within Google Analytics, and now we have the latest iteration: Google Optimize. While working on the integration of our A/B Testing Calculator with Google Optimize I was curious to see ... Read More

20-80% Faster A/B Tests? Is it real?

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

Risk vs. Reward in A/B Tests: A/B testing as Risk Management

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

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