Category Archives: Conversion Optimization

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…

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The Google Optimize Statistical Engine and Approach

Frequentist vs Bayesian A/B testing - Google Optimize

Updated Sep 17, 2018: Minor spelling and language corrections, updates related to role of randomization and external validity / generalizability. 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: […] Read More…

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

Risks vs Rewards in AB Testing

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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Costs and Benefits of A/B Testing: A Comprehensive Guide

Costs and Benefits in AB Testing

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 […] Read More…

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Statistical Significance for Non-Binomial Metrics – Revenue per User, AOV, etc.

Non-Binomial Significance - Revenue, Per User Metrics

In this article I cover the method required to calculate statistical significance for non-binomial metrics such as average revenue per user, average order value, average sessions per user, average session duration, average pages per session, and others. The focus is on A/B testing in the context of conversion rate optimization, landing page optimization and e-mail […] Read More…

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One-tailed vs Two-tailed Tests of Significance in A/B Testing

Two-tailed vs one-tailed test

The question of whether one should run A/B tests (a.k.a online controlled experiments) using one-tailed versus two-tailed tests of significance was something I didn’t even consider important, as I thought the answer (one-tailed) was so self-evident that no discussion was necessary. However, while preparing for my course on “Statistics in A/B Testing” for the ConversionXL […] Read More…

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