Alex Birkett

Alex Birkett

Alex Birkett is former Growth Marketer at CXL. Follow him on Twitter

A/B Testing Statistics: An Easy-to-Understand Guide

Testing tools are getting more sophisticated. Blogs are brimming with “inspiring” case studies. Experimentation is becoming more and more common for marketers. Statistical know-how, however, lags behind.

This post is filled with clear explanations of A/B testing statistics from top CRO experts. A/B testing statistics aren’t that complicated—but they are that essential to running tests correctly.

Here’s what we’ll cover (feel free to jump ahead):

  1. Mean, variance, and sampling;
  2. Statistical significance;
  3. P-values;
  4. Statistical power;
  5. Confidence intervals and margin of errors;
  6. Regression to the mean;
  7. Segmenting;
  8. Confounding variables and external factors.

And just in case you’re uncertain about why A/B testing statistics are so essential…

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13 Empirically Backed Form Design Best Practices

If you’re not following form design best practices, you might be leaving a significant amount of money on the table.

While forms aren’t the sexiest part of conversion optimization, they tend to be the closest to the money, the macro-conversions. Spending a little time optimizing forms can be some of the most important optimization work you can do.

Of course, best practices don’t work the same on all sites. It’s contextual. But generally, implementing form design tactics that work more often than not is a good way to get started.

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How to Avoid Being Deceived By Data

From the outside, it seems like data is impartial. It’s cold, objective, accurate.

In reality though it’s more complicated. In the hands of someone with an agenda, data can be weaponized to back up that viewpoint. Even in the hands of someone benevolent, data can be misinterpreted in dangerous ways.

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