Be cautious of measuring retention over too long a time period, as this can artificially inflate your retention metrics and mislead you about user engagement.

Using surveys to gauge product-market fit can be biased; instead, focus on measuring actual user retention.

Measuring retention is critical; if you don't have a product that retains users, you shouldn't focus on growth yet.

To determine if users are getting value from a product, simply measuring engagement, like watching more content, can be misleading; for example, watching fight videos may not reflect true user satisfaction.

When product teams focus solely on metrics like engagement or dwell time, they risk neglecting qualitative aspects such as content quality and user satisfaction, which can lead to long-term retention issues.

Inspecting metrics like adoption, engagement, and retention is essential to understand how users interact with an AI product and its effectiveness.

Tracking customer retention is essential; it helps you understand how many users continue to engage with your product over time, which is a key indicator of success.

Supercell believes that the most important metrics to focus on early in game development are retention and engagement, as they indicate whether players truly care about the game.

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.