I jumped straight to MRR and churn rate, which felt obvious in hindsight.
Start by categorizing KPIs into acquisition, retention, monetization, and engagement, then highlight the most critical ones for subscription health like churn, LTV, and MRR. Emphasize how these metrics interconnect and how you would instrument them as a software engineer, focusing on data pipelines and reliability.
Pro tip: Show that you understand the difference between leading and lagging indicators—for example, engagement metrics predict churn, while churn itself is a lagging indicator. Mention how you'd design systems to track these metrics in real-time to enable proactive decisions.
Group KPIs into acquisition (e.g., CAC, conversion rate), retention (e.g., churn, retention rate), monetization (e.g., MRR, ARPU, LTV), and engagement (e.g., DAU/MAU, feature adoption). This shows a structured approach.
Identify the most critical metrics for subscription health: churn rate, LTV, MRR, and customer retention. Explain why they matter and how they impact business sustainability.
Discuss how these metrics relate—e.g., high engagement reduces churn, which increases LTV and MRR. This demonstrates systems thinking.
Describe how you would implement tracking: data pipelines, event logging, dashboards, and ensuring data accuracy and timeliness. Mention tools like BigQuery, Dataflow, or Looker.
Conclude with how these KPIs drive product decisions and experiments (e.g., A/B testing to improve retention). Show that you connect metrics to business outcomes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.