Metrics 101, But Without The Non Sense | with Mengying, Notion Data Science Manager

This podcast episode features a discussion between two speakers, Mengying and another speaker, about the pragmatic use of metrics in data science, especially within startups and larger tech companies. They address common misconceptions about metrics, such as the idea that metrics must always be data-driven or that the primary goal is simply to drive metrics upwards, rather than improving user experience. The speakers explore the categorization of metrics, emphasizing the importance of leading versus lagging indicators, and provide a framework for brainstorming and selecting effective metrics that align with a company's mission and user value. They also highlight the necessity of regularly re-evaluating metrics to ensure they remain relevant to the evolving needs of the business and its user base, and the importance of qualitative data.