Articles exploring experiment integrity through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
3 articles
An A/A test pits two identical experiences against each other to validate your experimentation infrastructure. Learn what surprising A/A results reveal about the limits of significance testing and how to use them to calibrate your program.
Early peeking at A/B test results inflates false positive rates and leads to costly decisions based on noise. Learn why premature analysis destroys experiment validity and how sequential testing offers a legitimate alternative.
Sample Ratio Mismatch (SRM) is a critical diagnostic for A/B tests. When variant traffic splits deviate from expectations, it signals broken randomization that can invalidate lift and lead to costly, phantom wins.