You're analyzing user feedback data with your team. How do you reconcile conflicting interpretations?
Understanding diverse interpretations of user feedback data is a common challenge when working in the realm of Information Architecture (IA), which is the structural design of shared information environments. IA is crucial for ensuring that the data collected from users is organized, understood, and applied effectively to improve user experience. When your team faces conflicting interpretations of this data, it's essential to navigate through these differences to reach a consensus that benefits the project.