Most winning A/B test results are illusory

Marketers are questioning the value of A/B testing, asking: ‘Where is my 20% uplift? Why doesn’t it appear in the bottom line?’

What’s in this report?

This academic paper shows that badly performed A/B tests can produce winning results which are more likely to be false than true. At best, this leads to the needless modification of websites; at worst, to modification which damages profits.

We introduce three simple concepts which come as second nature to statisticians but have been forgotten by many web A/B testing specialists: ‘statistical power’, ‘multiple testing’ and ‘regression to the mean’. Armed with them, you will be able to cut through the misinformation and confusion that plague this industry.

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What you'll learn

  • The importance of statistical power
  • Why stopping tests early leads to false positives
  • How to perform validation tests to ensure accuracy
  • Why A/B tests tend to over-estimate uplift