Controlled experiments are the best scientific way to establish causality between your product features and customer impact. Establishing such causality allows you to only ship features that improve customer experience. This can make experiments the driving force behind your pace of innovation.
As you grow your pace of innovation, experiments also enable you to also measure the success of the features you ship and uncover unexpected side effects with every code change. This allows you to iterate faster in the short term, establish key business drivers, and make better, evidence-driven business decisions every day.
In comparison, relationships observed in historical metrics cannot be considered structural or causal because multiple uncaptured external and internal factors influence customer behavior. Historical metrics establish correlation, not causation.