Product sense is a critical skill for the [[product data scientist]]. Product sense includes two components - **empathy**: ability to understand the users problems and how the product solves (or could solve) pain points - **execution**: ability to use analytics and experiments to test solutions As a data scientist, it's critical to understand how [[product metrics]] contribute to successful [[product management]] in the context of the [[product vision]]. - Market sizing - Metric tradeoffs - Product modeling - Experiments ## product sense problem breakdown Product sense problems are often one of these flavors. - [[measuring product quality]] - metric investigation - product improvement Consider the key product elements to breakdown a product sense problem. - **Problem**: what problems do users face? - **Users**: who are the users? - **Onboarding**: what is the process of using the product for the first time? - **User Journey**: how do users typically use the app? - **Reward**: what is the benefit to the user? - **Retention**: how will it affect retention? - **Growth**: how might it lead to growth?