Metrics question
You are a PM at Uber or Ola. You have to upsell Uber Go to Uber Auto customers. How would you go about it? What product changes would you make?
- Vedantu
- Metrics
- Medium
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What this question tests
Growth and metrics thinking for a cross sell problem inside a ride hailing product.
How to approach it
- Clarify the goal: is this about margin (Go has better unit economics) or supply utilization during off peak hours.
- Segment Auto customers by price sensitivity and trip purpose, since not all will value Go's upgrade the same way.
- Identify the metric tree: awareness of Go, price perceived value gap, and conversion at the booking screen.
- Propose product changes: show a Go option with price difference at booking time, and time limited upgrade offers.
- Consider incentives: a first ride discount on Go for frequent Auto users.
- Define success as Auto to Go conversion rate and incremental revenue per upsold user, with a guardrail on overall booking rate.
What a strong answer includes
- Separates the business reason (margin or utilization) before designing the tactic, since the two goals lead to different solutions.
- Segments users by price sensitivity rather than blasting the same upsell to everyone.
- Gives an illustrative number, e.g. assumes a 15 percent price gap and tests whether a $0.50 discount closes 20 percent of the gap.
- Names a guardrail: total booking rate should not drop if some Auto seekers abandon rather than upgrade.
Common mistakes
- Proposing a blanket discount to everyone without segmenting by price sensitivity.
- Not stating the underlying business reason for the upsell push.
- No guardrail metric to catch users abandoning instead of upgrading.
Likely follow-up questions
- How would you identify which users are most likely to upgrade?
- What guardrail would stop you if bookings dropped?
- How would you test the discount size?
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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