Product design question
How would you improve the funnel for new users at Revolut?
- Revolut
- Product design
- Medium
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What this question tests
Product sense and funnel thinking: can you break a signup-to-first-value funnel into stages and prioritize the highest-leverage fix for a neobank.
How to approach it
- Define the funnel stages for Revolut: app download, signup/KYC, card activation, first top-up, first transaction.
- State an assumption about where the biggest drop-off likely is, e.g. KYC verification, since it's the most friction-heavy step for a bank.
- Ask what data exists per stage so you'd confirm rather than guess in a real setting.
- Propose a fix for the weakest stage, such as pre-filling KYC from a photo ID scan or reducing required fields.
- Consider a secondary lever like an incentive for the first transaction (e.g. fee-free first transfer).
- Define the success metric: signup-to-active-card conversion rate within 7 days.
What a strong answer includes
- Names KYC/identity verification as the likely biggest drop-off point for a regulated fintech, not a generic 'onboarding is confusing'.
- Proposes a specific fix: document auto-capture, progress indicators, or async verification so users can explore the app while KYC completes.
- Distinguishes activation (card ordered) from real activation (first transaction) and targets the true value moment.
- Gives an illustrative number, clearly marked as an assumption, e.g. 'if KYC drop-off is 30%, a 5-point improvement is worth X new active users'.
Common mistakes
- Treating 'funnel' as only the signup form and ignoring KYC/compliance friction specific to banking.
- Proposing fixes with no view on which stage has the largest volume of lost users.
Likely follow-up questions
- How would you validate that KYC is really the biggest drop-off before building anything?
- What guardrail metrics would you watch so a faster funnel doesn't increase fraud?
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More questions from Revolut
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