Why is relying solely on real-time stats insufficient for diagnosing long-term engagement problems?

Relying solely on real-time stats is insufficient for diagnosing long-term engagement problems because they only provide a snapshot of the current situation and lack the historical context needed to identify trends and patterns. Real-time stats, such as concurrent users (CCU) or current session length, can be useful for identifying immediate issues, such as server outages or game-breaking bugs. However, they don't provide insights into how player behavior is changing over time or why players are leaving the game in the long run. Diagnosing long-term engagement problems requires analyzing historical data over weeks, months, or even years. This data can reveal trends in player retention, session length, and monetization, allowing developers to identify the root causes of declining engagement. For example, a game might have a stable CCU, but a gradual decline in average session length over several months could indicate that players are becoming bored with the game's content. This trend would not be apparent from real-time stats alone. Analyzing historical data can also reveal the impact of specific game updates or events on player engagement. By comparing player behavior before and after these changes, developers can determine what's working and what's not. A comprehensive analysis of both real-time and historical data is essential for understanding the dynamics of player engagement and making informed decisions about game development.