Articles on A/B testing

In-depth articles on A/B testing with primary focus on statistical methods applied to online experimentation. Written in an accessible language targeted at conversion optimization practitioners the articles also go into deep technical topics where necessary.

Improving ROI in A/B Testing: the AGILE AB Testing Approach

After many months of statistical research and development we are happy to announce two major releases that we believe have the potential to reshape statistical practice in the area of A/B testing by substantially increasing the accuracy, efficiency and ultimately return on investment of all kinds of A/B testing efforts in online marketing: a free white […] Read more…

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The Importance of Statistical Power in Online A/B Testing

Statistical Power and Test Sensitivity

What is Statistical Power? In null-hypothesis statistical testing (NHST) – the procedure most commonly applied in A/B tests, there are two types of errors that practitioners should care about, type I and type II errors. Type I is the probability of the test procedure to falsely reject a true null hypothesis. Type II error is […] Read more…

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5 Reasons to Go Bayesian in AB Testing – Debunked

Frequentist vs Bayesian A/B Testing

As someone who spent a good deal of time on trying to figure out how to run A/B tests properly and efficiently, I was intrigued to find a slide from a presentation by VWO®’s data scientist Chris Stucchio, where he goes over the main reasons that caused him and the VWO® team to consider and […] Read more…

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The Bane of AB Testing: Reaching Statistical Significance

Illusory Results AB Testing

Now, this is not a new topic on this blog. I’ve discussed the issue of optional stopping based on “achieving” or “reaching” statistical significance in my Why Every Internet Marketer Should be a Statistician post more than two years ago and others have touched on it as well – both before and after me. However, the issue […] Read more…

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Bayesian AB Testing is Not Immune to Optional Stopping Issues

Fantasy vs real world in bayesian ab testing

Fantasy vs the Real World: Naive Bayesian AB Testing vs Proper Statistical Inference This post is addressed at a certain camp of proponents and practitioners of A/B testing based on Bayesian statistical methods, who claim that outcome-based optional stopping, often called data peeking or data-driven stopping, has no effect on the statistics and thus inferences […] Read more…

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Using Content Groupings for User Flow Analysis in Google Analytics

Order Chaos Content Groupings

In the first part of this article we talked about how to set up content groupings in Google Analytics and how to make sure it’s working as expected. In this part we’ll discuss the 4 main benefits of having content groupings defined. If I have to sum it up in one word, I would go with […] Read more…

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Setting up Content Groupings in Google Analytics

Planning

It’s been 2 years since content groupings first made it into Google Analytics, but it seems like this incredibly beneficial feature is still quite underused and poorly understood even among people otherwise familiar with the software. That’s why I decided to write a two-part guide of which you’re reading the first one – how to setup […] Read more…

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Overview of Books on Conversion Optimization, Web Analytics, SEO & PPC

Books on online A/B testing

This overview is a little different than most overeviews out there. It will focus on three specific basic statistical concepts and would show if and how well they are explored in 18 of the top books on Conversion Optimization, A/B testing, web analytics, SEO & PPC/AdWords. The three concepts this review focuses on are statistical […] Read more…

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Should you do A/A, A/A/B or A/A/B/B tests in CRO?

A/A Split Test

This question pops up often in more “advanced” discussion forums and blogs on Conversion Optimization and usually one (or several) of the following advices are given: Do an A/A test first in order to test your split testing framework. If the difference between the two is statistically significant at the decided level, then your framework is […] Read more…

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Why Every Internet Marketer Should Be a Statistician

Marketing as Fortune Telling

I’ll start this post right with the punch line: Internet marketing at its current state is dominated by voodoo magic. There, I’ve said it, and I’ve said it in bold italic so you know it must be true. Internet marketing is not as data-driven as most of us have been led to believe, it is […] Read more…

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Segmenting Data for Web Analytics – The Simpson’s Paradox

The Simpsons Paradox is an interesting issue for everyone dealing with data analysis, including web analytics specialists who deal with data in internet marketing. No matter which field you are in: conversion optimization, search engine optimization, search engine marketing or other, this paradox can give you an interesting insight. The paradox is about proper test design […] Read more…

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Analytics-Toolkit.com Official Launch – Today!

I am happy to announce the official launch of Analytics-Toolkit.com – the toolkit that makes analytics easier. I’m excited to present the results of over 2 years of development because I believe many web analytics specialists, SEO/SEM specialists, and internet marketers will find the tools in the toolkit valuable in their daily work. Most of […] Read more…

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