Product design question
Improve Robinhood (trading platform).
- Robinhood
- Product design
- Easy
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What this question tests
Product improvement for a consumer trading app, balancing engagement features against known criticism of encouraging risky behavior.
How to approach it
- Identify the user: retail investors ranging from long-term holders to active traders, many drawn by Robinhood's simple, commission-free interface.
- Name the pain point: users often lack context for making informed decisions, since the app has historically prioritized simplicity over education and risk context.
- Propose an improvement: in-context education and risk indicators shown at the point of a trade, such as volatility history or a plain language summary of the position's risk.
- Prioritize this over new trading features, since past criticism of gamified, low-friction trading has created real regulatory and reputational risk for the company.
- Define success as reduction in impulsive trade reversals (buying and selling within minutes) and improved user reported confidence in trades, without significantly reducing platform usage.
What a strong answer includes
- Directly addresses Robinhood's known real world criticism around encouraging impulsive trading, rather than proposing purely growth-focused features.
- Proposes a measurable proxy for impulsive behavior, rapid buy-sell reversals, instead of a vague 'improve education' statement.
- Balances the fix against business impact, checking that added friction does not tank core engagement metrics.
Common mistakes
- Proposing only new trading features that increase activity without addressing known user harm concerns.
- Ignoring the business tension between adding friction for user protection and maintaining trading volume.
Likely follow-up questions
- How would you measure whether users found the new risk information actually helpful versus annoying?
- How would you balance this against pressure to keep trading volume high?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop