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Meta·Software Engineer·Hiring Manager Screen·Intermediate

Intermediate
May 2026

Summary

Interviewed for a BA role at Meta, got a metrics question that sounds straightforward but really isn't once you're sitting there trying to figure out which numbers actually matter.

Questions Asked (1)

Q1

What KPIs would you track to measure the overall health of a company?

Product Analytics & MetricsProduct Strategy
Author's notes

I went straight to revenue and DAU and immediately felt like I was listing things off a Wikipedia page.

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AI HintsAI Generated

Suggested Approach

Start by acknowledging that KPIs depend on the company's business model and stage, then propose a balanced framework covering growth, engagement, monetization, and reliability. For a software engineer role at Meta, emphasize how engineering directly influences these metrics and how you would instrument and monitor them.

Pro tip: Tie each KPI to a specific engineering initiative you could own, showing you think like an owner who connects code to business outcomes. Mention that you'd validate metrics with A/B tests and guard against vanity metrics.

1. Clarify Business Context

Ask about the company's business model, stage, and primary goals to tailor KPI selection. This shows you avoid one-size-fits-all answers.

2. Categorize KPIs

Group metrics into acquisition, engagement, monetization, retention, and reliability. This ensures comprehensive coverage of company health.

3. Prioritize and Define

Select 1-2 key metrics per category and define them precisely (e.g., DAU/MAU, LTV, p95 latency). Explain why they matter for the company's strategy.

4. Connect to Engineering

Describe how engineering decisions impact each KPI and how you would instrument, monitor, and experiment to improve them.

5. Monitor and Iterate

Explain how you'd set up dashboards, alerts, and regular reviews to track trends and adapt as the company evolves.

Key Points to Mention

  • North Star Metric and how it aligns teams
  • DAU/MAU ratio as a measure of engagement and stickiness
  • Customer Acquisition Cost (CAC) and Lifetime Value (LTV) for sustainable growth
  • Retention and churn rates to gauge long-term health
  • System reliability metrics like uptime, p95 latency, and error rates
  • A/B testing and experimentation to validate metric improvements

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.