I fumbled this a bit because I'd already talked about the product but hadn't really touched metrics the first time around.
Structure your answer around the product's North Star metric and the key input metrics that drive it, explaining how you instrumented, tracked, and iterated using data. Emphasize the 'why' behind each metric choice and how you used analytics to make product decisions, not just report numbers.
Pro tip: Tie your analytics to a specific product decision or A/B test outcome, showing you understand correlation vs. causation and the limitations of data. Meta values a growth mindset, so highlight what you learned from a metric that didn't move as expected.
Explain how you identified the product's North Star metric and the key input metrics that influence it, ensuring alignment with business goals.
Detail how you set up event tracking, logging, and dashboards to capture user behavior, including any tools used (e.g., Amplitude, Mixpanel, SQL).
Walk through the analysis techniques you applied, such as cohort analysis, funnel analysis, or segmentation, to uncover patterns and opportunities.
Explain how the analytics informed specific product changes, experiments, or prioritization, and the resulting impact on metrics.
Describe how you validated the changes through A/B tests or other methods, and what you learned to inform future iterations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.