Assume you are interviewing for a Product Growth Analyst role at Meta. Answer the following product growth and analytics cases. For each case, clarify the goal, define the primary metric and guardrails, break the problem into a funnel, identify what data you would inspect first, propose hypotheses, prioritize one intervention, and explain how you would validate impact. 1. **Improve Instagram Stories viewer engagement.** - How would you improve the Instagram Stories viewing experience? - What data would you examine first? - What product ideas would you generate? - Pick one idea and explain how you would test it. 2. **Double Boosted Posts MAU in 6 months.** - Assume Boosted Posts MAU is defined as the number of distinct users or businesses that launch at least one boosted post in a calendar month. - How would you determine whether doubling MAU in 6 months is realistic? - Which levers would you target across acquisition, activation, retention, and resurrection? - What trade-offs and guardrails would matter? 3. **Grow the number of active Reels creators.** - Define what an active creator means. - How would you diagnose supply-side bottlenecks in the creator funnel? - What interventions would you prioritize to increase durable creator growth rather than only short-term posting spikes? 4. **Increase logged-in users on the mobile Facebook app.** - Logged-in user count on the mobile Facebook app is declining. - Focus your analysis on the login funnel, session persistence, password reset, and authentication friction. - How would you determine whether the issue is a measurement problem, a product bug, a security or anti-abuse trade-off, or a real behavioral change in users? In all cases, discuss segmentation, possible confounding factors, and when you would use an A/B test versus a quasi-experimental or diagnostic approach.