Balancing Hands-On Data Analysis and Intuition in Product Decisions

The interviewer wants to know two things: whether you enjoy working with data yourself, and whether you favor data or intuition when making product decisions. Answer both and back up your stance with an example. ```hint Think about where each one failed you Recall a decision where the numbers were missing or misleading, and one where your gut was wrong; what set those situations apart is the core of your answer. ``` ### Clarifying Questions - Does working with data here mean writing my own queries and building dashboards, or reviewing analyses that an analyst team prepares? - Should the example be a decision where the data and my intuition pointed in opposite directions? - Are you asking about decisions on a mature, high-traffic product, or on new initiatives where little data exists yet? ### What a Strong Answer Covers - A direct answer to both questions: comfort with hands-on data work and a clear stance on data versus intuition - The conditions under which the candidate gives data or judgment more weight (data availability, reversibility, novelty of the problem) - Concrete evidence of hands-on analysis: tools used, metrics examined, an analysis that changed a decision - An example where data and intuition were in tension and how it was resolved - Awareness of data's limits, such as instrumentation errors, misleading aggregates and short-term metrics ### Follow-up Questions - Tell me about a time the data pointed one way and you decided the other way. What happened? - An A/B test comes back flat, but you still believe in the feature. What do you do next? - When you join a new product team, which data do you pull first, and why?