Bayesian versus Frequentist Statisticians: the war is real

Imagine that you wake up in the one morning and you don’t remember anything from your previous life. You’ve erased all memories from your previous days.

Pretty intense and terrifying, huh?

Well, that’s how Bayesian statisticians describe frequentist colleagues because frequentist statisticians do not use any prior knowledge. Everything you learn about the world is through the lens of events that are happening at the moment and currently.

Michael Hochster explains;

“The essential difference between Bayesian and Frequentist statisticians is in how probability is used.”

As interest grows in conversion optimization and A/B testing, marketers are always searching for a new design that will generate significant uplifts in conversion rates. Because the majority of AB tests fail to produce any meaningful results, many marketers are too eager to declare a winner for a split test.

So, even in the few instances where a testing software declares a winner, there is a good chance that you merely identified a false positive.

How do you avoid that?

You start by having a good handle on A/B testing statistics to ensure that your data is collected and analyzed …

Did you know anywhere from 80% to 90% percent of A/B tests do not produce any significant results?

In fact:

Only 1 out of 8 A/B tests drive significant change.

Done incorrectly, some marketers have begun to question the value of A/B testing…

…their A/B test reports an uplift of 20% and yet, the increase reported by the AB testing software never seems to translate into improvements or profits.

The reason?

“Most winning A/B test results are illusory.” (Source: Qubit)

Furthermore, the majority of arguments that call for running A/A testing consider it a sanity check before you run …

You must cover all the bases to get reliable results from your A/B tests.

A/B testing mimics scientific experiments, and similarly will not provide you a 100% certainty in 100% of tests that you run. Only few marketers are aware of the limitations of the method and know how to run it to get valid results and minimize the risk of false positives and false negatives.

That’s why Martin Goodson, now the Chief Scientist at Evolution AI, wrote a paper called “Most Winning A/B Test Results Are Illusionary.” In his paper, he explained that badly performed A/B tests are more …

“Why do I need to learn about statistics in order to run an A/B testing?” You may be inclined to wonder, especially considering that the testing engine supplies you with data to make a judgement on the statistical significance of the test, correct?

As a matter of fact, you have plenty of reasons to learn statistics.

If you’re conducting A/B tests, you need to understand some basics about statistics to validate your tests and their results.

Nobody wants to spend time, money and effort on something that will turn out useless at the end. To use A/B testing efficiently and effectively, …

How to increase SAAS converstion rate and what to test next in your SaaS website?

Great question. Increasing the conversion rates of a SaaS (software as a service) website is part science, part art. That means, you need to take a look at the numbers and data from visitors’ behavior, while also looking for unique insights and solutions to some of the problems you uncover with the data.

To help you out with inspiration for future testing, we compiled real-life examples and case studies of successful and surprising A/B tests on SaaS websites.

But, first, a fundamental rule of thumb …

“Should I run an A/B test or a Multivariate test?”

This simple yet fundamental question always pops up in planning for conversion rate optimization. In this post, you will know about the advantages and disadvantages of A/B Testing and Multivariate testing and when should you use A/B testing or Multivariate testing.

A/B testing is the default and most common procedure in CRO programs. In some cases, though, running a multivariate test can add a significant value. Other times, you have room for both tests interchangeably.

The great benefit of testing? You give your visitors a voice in the design process.

…

2016 was a bold year for Invesp. It was a year of amazing successes. But, also, of rough failures. I have always believed that you must be willing to embrace failure if you are looking to achieve big wins.

While embracing failure applies to many things in life, it is  truer for anyone doing CRO.

In 2016, we ran a total of 512 A/B tests through our various projects helping top online brands increase their website conversion rates.

Most of our tests are medium to highly complex tests. Since we have been doing conversion optimization for over 11 years, we …