revolut·Product Manager·Onsite - Product Sense / Strategy·Intermediate

Intermediate

May 2026

Summary

Revolut PM interview, onboarding team focus. One case-style question about moving a conversion metric under a tight timeline. Pretty product-heavy, no behavioral fluff.

Questions Asked (1)

You're a PM on the Onboarding team. How would you drive a 15% increase in onboarding funnel conversion within 3 months?

Product Analytics & MetricsA/B Testing & ExperimentationProduct Strategy

Author's notes

The time constraint is what made this hard.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the onboarding funnel definition and current conversion rates, then propose a data-driven approach to identify the biggest drop-off points. Prioritize high-impact, low-effort experiments using a framework like ICE, and outline a 3-month plan with clear milestones and measurement.

Pro tip: Emphasize the importance of setting up a robust experimentation framework and guardrail metrics to avoid sacrificing long-term user quality for short-term conversion gains.

1. Clarify and Baseline

Ask clarifying questions to define the onboarding funnel stages, current conversion rates, and any constraints. Establish a baseline to measure progress.

2. Identify Drop-offs

Analyze funnel data to pinpoint the largest drop-off points and segment users to understand where the biggest opportunities lie.

3. Generate Hypotheses

Brainstorm potential improvements for each drop-off point, drawing from user research, competitive analysis, and best practices.

4. Prioritize Experiments

Use a prioritization framework (e.g., ICE) to select high-impact, low-effort experiments that can be executed within 3 months.

5. Execute and Measure

Run A/B tests, measure results against baseline and guardrail metrics, and iterate quickly to achieve the 15% increase.

Key Points to Mention

Define the onboarding funnel and key metrics (e.g., sign-up completion, KYC pass rate, first transaction).
Use data to identify drop-off points and segment users (e.g., by acquisition channel, device, geography).
Prioritize experiments using a framework like ICE (Impact, Confidence, Ease).
Run A/B tests with proper sample sizes and statistical significance.
Monitor guardrail metrics (e.g., long-term retention, support tickets) to avoid negative side effects.
Set a 3-month roadmap with weekly milestones and clear success criteria.

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