Experiments
Experiments are structured activities designed to support or refute a hypothesis by testing whether a specific change has the expected impact. In product discovery, the term "experiments" typically refers to large-scale randomized controlled experiments (like A/B tests) that measure the impact of something after it's been built.
What's the difference between experiments and assumption tests?
Teams rarely have time to run real experiments in discovery. They can run large-scale randomized controlled experiments, also known as A/B tests, after they build something, but that's only if they have enough traffic. And this is not the best discovery activity.
Teams don't want to do all the work to build something before they learn they built the wrong thing. This is why assumption testing makes more sense during discovery—assumption tests are faster and take less work.
Assumption tests are used in discovery when trying to decide between ideas. Experiments are used to measure the impact of what teams built.
When should teams use experiments?
While experimentation is becoming more pervasive in product development, teams need to be smart about when and how they use experiments. Teams should use lighter-weight assumption tests during discovery and save full experiments for measuring the impact of what they deliver.
Learn more:
- Assumption Testing: Everything You Need to Know to Get Started
- Hypothesis Testing
Related terms:
- Assumption Testing
- Hypothesis
- Prototyping
- Discovery
Last Updated: October 25, 2025