Articles on cro

The Cost of Not A/B Testing – a Case Study

The cost of not a/b testing

Most of the time when discussing A/B testing, regardless of context, we discuss costs such as the expense of running an experimentation program, of shipping ‘winners’ to production. Only rarely do I see references to the less obvious, but usually more important costs in terms of opportunity cost (incurred during testing) and the cost of […] 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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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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Efficient AB Testing with the AGILE Statistical Method

AGILE AB Testing

Don’t we all want to run tests as quickly as possible, reaching results as conclusive and as certain as possible? Don’t we all want to minimize the number of users we send to an inferior variant and to implement a variant with positive lift as quickly as possible? Don’t we all want to get rid of […] Read more…

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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 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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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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