In-depth articles on A/B testing, statistics, landing page psychology, and how autonomous experimentation works under the hood.
Your A/B test reached statistical significance. Champagne? Not yet. If the traffic split between control and variant drifted from what you configured, every number on that results screen is a lie.
Both camps claim the other is wrong. The truth is that they answer different questions. Once you understand that, you can use both correctly — and stop misinterpreting p-values.
Most landing page copy is written to inform. The best landing page copy is written to persuade. Cialdini's six principles of influence are the foundation — and they are directly testable.
Most A/B tests are stopped too early. The result looks significant, someone gets excited, and the experiment is called. Two weeks later, the lift has vanished. Here is the math that prevents this.
You ran a test. One variant is up 40%. The team is ecstatic. Twyman's Law says: the more surprising the result, the more carefully you should check your data before celebrating.