Feature usage patterns reveal how users interact with specific product functionalities over time. These patterns help identify the most valuable features, discover usage barriers, and understand the typical progression of feature adoption. Initial feature discovery often leads to experimental usage, followed by either sustained adoption or abandonment.

Feature adoption typically follows distinct phases during the user journey. Core features see immediate adoption and regular usage, while advanced features may experience delayed discovery or selective usage. Usage data shows whether features complement each other, compete for attention, or serve distinct user segments at different stages of their journey.

Cohort analysis of feature usage unveils how different user segments interact with functionalities. New users might gravitate toward basic features, while power users exploit advanced capabilities. This segmentation enables teams to optimize onboarding flows, improve feature discovery, and identify opportunities for user education and feature enhancement.