It's important to observe how people use software in real time, as this can provide valuable insights that metrics alone cannot capture. Relying solely on metrics to understand user behavior is like observing raw data from a radio telescope instead of experiencing the night sky directly.

It's crucial to analyze quantitative data, like user logs and retention curves, to understand how your product is actually being used, rather than relying solely on user feedback.

Our narrative for the Up24 revolves around tracking, understanding, and acting on personal health data to improve user engagement.

The goal is to create a system that can analyze vast amounts of health data and provide personalized insights for better health management.

To enhance user experience, we built a system that helps users understand how their actions, like working out at a specific time, can lead to better sleep quality, thus encouraging healthier habits.

To collect data, instrument your tracking by defining user events, such as signups and video plays, to understand user behavior and engagement.

We need to connect genetic signatures with health data to make meaningful predictions about individual health and lifestyle choices.

AI models need to develop a deeper understanding of users beyond single interactions, fostering empathy and contextual awareness to enhance long-term engagement.

Personas are a valuable tool for understanding specific user needs and tailoring the product accordingly.