Metrics question
how much more or less do you pay drivers per trip (by changing Lyft’s take)? Your goal is to maximize net revenue for the next 12 months on this route.
- Metrics
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Pricing and marketplace balance reasoning: can you optimize a two sided rate change for net revenue while accounting for driver supply elasticity.
How to approach it
- Clarify the goal precisely, maximizing net revenue on this specific route over 12 months, which means balancing rider fare revenue against driver payout cost and supply availability.
- Model the trade off: paying drivers less per trip increases margin per ride immediately but risks drivers leaving for other routes or platforms, reducing ride availability and future revenue.
- Propose testing incrementally, small payout adjustments in a controlled experiment on this route, measuring driver supply response, like online hours or acceptance rate, before committing to a large change.
- Watch for a tipping point, since driver payout cuts often show a threshold effect, minor cuts show little supply drop, but past a certain point, drivers leave rapidly.
- Balance with rider side elasticity too, since if driver payouts drop and wait times rise, riders may leave for competitors, hurting revenue from both sides.
- Recommend a conservative, monitored adjustment rather than a large one time cut, checking supply and demand metrics weekly before further changes.
What a strong answer includes
- Treats this as a two sided elasticity problem, not just a simple cost cutting exercise, correctly capturing the real risk.
- Proposes incremental testing with a tipping point framework, rather than guessing a single optimal number upfront.
- Connects driver payout changes to rider experience, showing the marketplace is interconnected, not two independent levers.
Common mistakes
- Recommending a large payout cut based only on short term margin math, ignoring driver supply response.
- Ignoring the downstream effect on riders if wait times increase from reduced driver supply.
Likely follow-up questions
- How would you detect the tipping point before it causes a major supply drop?
- How would this recommendation differ for a route with strong competitor presence nearby?
More metrics questions
- How do you define success for Yelp reviews?Google · Metrics · Medium
- Utilization went down by 45% on app XYZ in Italy for the month of August. Give a reason why and draft a plan to fix it.Spotify · Metrics · Medium
- You launched a new signup flow to encourage new users to add more profile information. A/B test results indicate that the % of people that added more information increased by 8%. However, 7 day retention decreased by 2%. What do you do?Google · Metrics · Hard
- Define the metrics for YouTube search.Google · Metrics · Medium
- You walk in to your office and find that Google cloud subscription has gone down by 20%. What do you do as a product manager?Google · Metrics · Medium
- What would be the top six metrics for WhatsApp? Now pick one from the six. Tell me three things you would do to improve that metric.Google · Metrics · Medium
More questions from Google
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop