Based on [quantitative/qualitative insight].
We predict that [product change] will cause [impact].
We will test this by assuming the change has no effect (the null hypothesis) and running an experiment for [X week(s)].
If we can measure a Y% statistically significant change in [metric] then we reject the null hypothesis and conclude there is an effect.
The Hypothesis Kit was developed by Rik Higham and Colin McFarland, with contributions from David Pier, Lukas Vermeer, Ya Xu and Ronny Kohavi. “Design like you’re right, test like you’re wrong” props to Jane Murison and Karl Weick. Original Hypothesis Kit from Craig Sullivan.