Product design question
How would you improve the Revolut referral program?
- Revolut
- Product design
- Easy
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What this question tests
Tests growth-loop optimization on an existing feature: can you identify a specific friction or incentive gap in a referral program rather than a generic 'increase the reward' answer.
How to approach it
- Clarify the current referral mechanic: assume a standard give-and-get cash or fee-waiver reward for inviting a friend to open a Revolut account, and identify where it likely underperforms.
- Identify likely friction points: unclear reward timing (does the referrer get paid immediately or after the friend completes KYC and a first transaction), and low visibility of the referral feature within the app.
- Prioritize reducing reward-timing ambiguity first, since delayed or unclear payout is a common reason referral programs underperform even when the headline reward is generous.
- Add a double-sided, milestone-based incentive: reward both referrer and referee at clear, tracked milestones (account opened, first transfer, card activated) rather than a single vague reward, increasing trust and completion.
- Increase visibility: surface the referral prompt at high-intent moments, like right after a user successfully makes their own first transfer, when they are most likely to recommend the app.
- Define success as referral conversion rate (invited to completed sign-up) and viral coefficient (referrals generated per existing user), not just number of invites sent.
What a strong answer includes
- Focuses on payout clarity and timing as the likely biggest lever, a well-known real-world driver of referral program performance, rather than jumping straight to increasing the reward amount.
- Proposes milestone-based rewards, which reduces both fraud risk and user confusion compared to a single all-or-nothing payout.
- Identifies a high-intent trigger moment (after the user's own successful transfer) for surfacing the referral prompt, rather than a generic settings-menu placement.
- Picks viral coefficient specifically as a metric, which is the correct way to measure whether a referral program is actually compounding growth.
Common mistakes
- Defaulting to 'increase the cash reward' without diagnosing why the current program underperforms.
- Ignoring reward-timing clarity and trust, a major real driver of referral program conversion.
- Measuring success by invites sent rather than completed referrals or viral coefficient.
Likely follow-up questions
- How would you prevent referral fraud with a milestone-based reward structure?
- How would you personalize the referral incentive by user segment?
- What would you do if increasing the reward amount did not improve conversion?
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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