Segmenting Visitors For Better Testing Results


Not all visitors are created equal; therefore you shouldn’t pretend they are in your tests. To optimize your testing plan, you should recognize that different visitors to your website have different characteristics and different goals.

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A/B or MVT: When to Choose Which Type of Test?


An important aspect of conversion optimization testing is deciding on which type of experiment you’re going to run. This basically boils down to two different options, A/B testing or Multi Variate Testing.

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Writing a Good A/B Testing Hypothesis


A sound hypothesis is what makes or breaks any conversion optimization experiment. Without having a relevant, unambiguous, measurable and specific hypothesis to start off with, you’re basically groping in the dark with your experiment.

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Validating Experiments Before Running Them


Most people start optimizing their website by testing the first thing that comes to mind. While this process seems like an efficient way of running tests, it isn’t an effective solution. In order to improve this process, you should make sure that tests are validated and founded in qualitative and quantitative research.

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Planning Conversion Optimization Experiments


Every experiment (from a simple 2-variation A/B test to a complex multi-page MVT) starts with planning. In this article I suggest you should pay attention to the following aspects while making your testing plan.

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Conversion Hotel 2014 - Keynotes, Tweets, Photos

Conversion hotel 2014

Conversion Hotel is a three-day event about online optimization, fun and beer at a Dutch island called Texel. Topics include online marketing, persuasion, conversion rate optimization and UX.

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Top 10 Best Conversion Optimization Blogs

Top 10 blogs

Scattered around the web there is a great number of conversion optimizations blogs these days. While some of them offer great material, others unfortunately stay behind and fail to produce innovatory content on a regular basis.

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Is Repeating A/B Tests Worthwhile?

Car wreck

What will the results be when an A/B test is repeated, and is it worthwhile to repeat old tests? The critical question that should be posed is: Why are you expecting different results compared to when the test was run the previous time? Is there any reason to suspect that external factors such as the website or even the entire organization have changed substantially?

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