When deciding to roll out a new feature, it's challenging to observe the impact on key metrics without splitting the world into parallel universes. Instead, experimentation helps approximate this by randomly selecting groups of users and delivering different experiences to them, allowing for observation of results. This approach is valuable in various scenarios, including stakeholder disagreements, replicating another product team's win, when UX research is inconclusive, sales team pressure, engineer-driven ideas, efforts between MVP and full feature, tech licensing decisions, directive from above, developing personas, and big, impactful ideas. Experimentation provides a way to test hypotheses, gather evidence, and make data-driven decisions, ultimately driving business outcomes and informed product development.