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Meta·Product Manager·Onsite - Product Sense / Strategy·Senior

Senior
Apr 2026

Summary

Meta PM interview with a product strategy question about Instagram. Just the one question but it had a lot of layers to it, more than I expected going in.

Questions Asked (1)

Q1

You're the PM for Instagram. How would you approach the decision of whether to invest in a verification badge feature?

Product StrategyRoadmap PrioritizationPricing & Monetization
Author's notes

This felt deceptively simple and I kind of walked into it too fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the goal of verification badges—whether to increase trust, reduce impersonation, or create a revenue stream—and then evaluate the decision through a structured framework that weighs user value, business impact, and risks. Use data and user research to inform trade-offs, and consider both short-term and long-term implications for Instagram's ecosystem.

Pro tip: Acknowledge that verification is a double-edged sword: it can enhance trust but also create a two-tier system that alienates users; propose a phased approach with clear success metrics to mitigate risks.

1. Define Objectives and Success Metrics

Clarify what problem the verification badge solves (e.g., authenticity, safety, monetization) and define measurable goals such as reduced impersonation reports or increased creator engagement.

2. Assess User and Business Value

Evaluate how the feature benefits users (trust, credibility) and the business (revenue, retention), and consider potential negative impacts like user backlash or inequity.

3. Analyze Feasibility and Risks

Examine technical, operational, and policy challenges, including verification criteria, scalability, and potential for abuse or legal issues.

4. Explore Monetization and Pricing Models

If considering paid verification, analyze willingness to pay, competitive landscape (e.g., Twitter Blue), and impact on brand perception and user trust.

5. Recommend and Prioritize

Synthesize findings into a clear recommendation, prioritizing based on impact and effort, and propose a phased rollout with metrics to track success.

Key Points to Mention

  • User trust and safety: reducing impersonation and misinformation
  • Monetization potential: subscription revenue and creator economy
  • Equity and inclusivity: avoiding a two-tier system that disadvantages regular users
  • Competitive landscape: how other platforms (Twitter, TikTok) handle verification
  • Technical and operational feasibility: scalable verification processes
  • Metrics: define KPIs like number of verified accounts, revenue, user sentiment

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