PM Interview: Tackling Trade-Off Questions

Introduction

• Presenter: Diana, Senior Product Manager at a tech company in Silicon Valley
• Topic: How to tackle trade-off questions in PM interviews
• Purpose: Provide a robust framework and detailed example to address trade-off questions like "How would you decide between launching X vs. Y?"

Diana's Framework (Updated)

Six-Part Step

1. Mission, Goal, and Hypothesis
   • Connect product goal to company's mission
   • Explain hypothesis: Why consider these options?
2. Success Metrics
   • Define essential success metrics
   • Metrics for analysis in A/B testing
3. Hypothesized Impact
   • Expected impact of options on key metrics
4. Other Options
   • Additional testing options
5. Design A/B Test
6. Analyze Metrics
   • Decision: Ship, No Ship, or Retest

Detailed Example: Instagram Stories Duration (24 Hours vs. 48 Hours)

Step 1: Mission, Goal, and Hypothesis

• Mission: Capture and share the world's moments
• Goal: Lower barrier to sharing, improve engagement
• Hypothesis: Longer duration -> More engagement, more content

Step 2: Success Metrics

• Engagement Metrics:
  • Number of stories with at least one engagement/week (reactions, DMs)
  • Average time spent on stories per weekly active user
• Creator Metrics:
  • Total number of weekly active creators/stories vs. weekly active users
  • Average number of stories posted per week
• Consumer Metrics:
  • Number of story impressions
  • Number of stories clicked (CTR)
  • Number of stories watched (watch time > 3 seconds)
• Overall Platform Health:
  • Average time spent per weekly active user
  • Number of weekly active users

Step 3: Hypothesized Impact

• Positive Impact Expectations:
  • Increase in stories with engagement
  • More time spent on stories
  • Increased weekly active users

Step 4: Additional Testing Options

• Allow users to choose 24 vs. 48 hours
  • Default to 48 hours, optional 24 hours
  • Benefit: Cater to power users who prefer fresh content

Step 5: Design A/B Test

• Control Group: Existing 24-hour stories
• Test Groups:
  • Option 1: 48-hour stories
  • Option 2: Default 48 hours, with 24-hour option
• Success Criteria:
  • Unbiased results, proper randomization
  • Sufficient user sample size and test duration for statistical significance
  • Cooperation with data scientists for power calculations and monitoring results

Step 6: Analyze Metrics

• Ship Decision Criteria: Highest incremental impact, no major metric regressions
• No Ship Criteria: Negative impact, significant regressions
• Retest Criteria: Lack of statistical significance, neutral but positive directional results

Bonus Tips

• Prioritization: Focus on key metrics impacting decisions
• A/B Test Design: Ensure tests are unbiased and statistically significant

Conclusion

• Understanding and effectively using a structured framework is key to tackling tough trade-off questions
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