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Product Management Trade-off Question: Facebook Marketplace product recommendations versus organic listings visibility

Asked at Meta

15 mins

How would you decide if you should build a "Products you might want to buy" feature on the Facebook Marketplace newsfeed?

Product Trade-Off Medium Member-only
Data Analysis Feature Prioritization Experiment Design Social Media E-commerce Advertising
User Engagement E-Commerce Facebook Product Trade-Offs Recommendation Systems

Introduction

Deciding whether to build a "Products you might want to buy" feature on the Facebook Marketplace newsfeed is a critical product trade-off that could significantly impact user engagement and revenue. This scenario involves balancing user experience, business goals, and technical feasibility. I'll analyze this trade-off by examining the context, potential impacts, and key metrics, then design an experiment to inform our decision.

Analysis Approach

I'd like to outline my approach to ensure we're aligned on the key areas I'll cover in my analysis.

Step 1

Clarifying Questions (3 minutes)

  • What's the current user engagement rate on Facebook Marketplace?

  • Why it matters: Understanding baseline engagement helps assess potential impact.
  • Hypothetical answer: 30% of Facebook users engage with Marketplace monthly.
  • Impact: Low engagement might justify new features to boost interaction.
  • How does Marketplace currently contribute to Facebook's revenue?

  • Why it matters: Aligns feature with business goals and revenue strategy.
  • Hypothetical answer: Marketplace contributes 5% of Facebook's ad revenue.
  • Impact: Higher revenue contribution could prioritize this feature.
  • What user segments are most active on Marketplace?

  • Why it matters: Identifies target audience for the new feature.
  • Hypothetical answer: Millennials and Gen X are most active, primarily for second-hand goods.
  • Impact: Feature design should cater to these segments' preferences.
  • What's our current recommendation system's accuracy for user preferences?

  • Why it matters: Assesses technical feasibility and potential effectiveness.
  • Hypothetical answer: 70% accuracy in predicting user interests across Facebook.
  • Impact: Higher accuracy could increase confidence in feature success.
  • Is there a specific timeline or resource constraint for this project?

  • Why it matters: Helps prioritize and scope the feature appropriately.
  • Hypothetical answer: 3-month timeline with a dedicated team of 5 engineers.
  • Impact: Tight constraints might necessitate a phased approach or MVP.

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