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I have meant to write this post for a long time. There has been a lot written about one-tailed vs. two-tailed tests. However, most of the articles approach the topic from a purely statistical perspective providing many formulas but do not show how to do the calculations. Others articles approach the issue from a high-level business perspective. So, here is my attempt to delve deep into the topic. Some sections in this article are heavy on stats and formulas. If you are not interested in these, you can skip them! Special thanks to our data sciences team …

Conversion optimization, much like most SEM activities, touches all verticals and various channels. Each company has its own unique experience, and we always emphasize, no two projects are ever the same. It’s that uniqueness which ensures CRO will succeed for that organization. Nonetheless, projects are brought together with a common thread: the documentation and deliverables that are produced as a result of the research and effort are pretty standard.

Much to my own chagrin, most of our potential clients say that what most CRO agencies say they offer sounds pretty much the same. Obviously, as an agency co-owner, I …

There are hundreds of case studies and examples on AB testing, explaining what makes it highly useful for conversion optimization. While AB testing is important, it is a mere component of the overall CRO process. What’s critical to keep in mind is not dive into AB testing right away until you know everything about interpreting, analyzing, and understanding test results.

AB testing isn’t foolproof and like anything in statistics, results can simply be wrong. But the more you know about what makes a test valid, and basic statistical concepts, the more likely it is that you will not face …

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Test this, test that…and always be testing.

As I listened to one speaker after the next, I wondered why a client would hire them in the first place. If you are a CRO agency, and the best advice you can provide to attendees in a conference is to test this and test that, then I am not sure why these companies would hire you in the first place.

All you need to do is start AB testing, find that one fantastic test that will take you from absolute anonymity to an overnight web success…that is what brings most …

A conversion optimization project is typically divided into four different phases that intertwine:

Scrutinize stage: You conduct various activities to determine possible testing areas on a platform or campaign Hypothesis: you create a hypothesis for the different testing ideas identified during the scrutinize phase Implement: you validate your hypothesis through the process of AB or usability testing Propagate: you look for insights, share them within the organization, across marketing channels and verticals

As you go through the process of identifying conversion issues on your website (scrutinize), you can easily identify anywhere from 150 to 250 possible test scenarios. Shana Rusonis …

Wild guesses and opinions often only result in delusional outcomes. Though opinions are by far the most widely accepted truth, they rarely are factual. It is a better practice to lean on deductive reasoning and logic instead of guesswork. But how do you arrive at what is labeled as a fact or a valid statement? Experimentation is the key.

Businesses realize the importance of scientific experimentation and testing. Many product-based enterprises have imbibed experimentation in their organizational culture. The reason – innovation cannot result without experimentation. Moreover, though there are millions of ideas that spur every minute, every hour, it …

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 …