Metrics question
How would you increase the revenue of Swiggy by 4x?
- SuprDaily
- Metrics
- Hard
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What this question tests
Aggressive growth-target metrics thinking: can you break a big multiplier (4x revenue) into believable component levers rather than one hand-wavy plan.
How to approach it
- Break revenue into a formula: revenue = active users x order frequency x average order value x take rate.
- State current assumptions for each lever (illustrative, since real figures aren't given) to see which has the most room to move.
- Identify the biggest lever for a grocery-delivery-style business: order frequency, since habitual reordering compounds faster than one-time AOV increases.
- Propose initiatives per lever: subscription/membership for frequency, category expansion for AOV, and geographic expansion for user count.
- Acknowledge 4x is aggressive and likely needs a combination, e.g. 1.5x frequency x 1.3x AOV x 1.5x user growth x 1.3x take rate improvement.
- Define the metric to track progress: month-over-month revenue growth rate against the compounded target.
What a strong answer includes
- Decomposes the 4x target into a multiplicative formula instead of proposing random growth ideas.
- Shows the math of how several moderate levers (not one heroic lever) compound to reach 4x, which is realistic.
- Prioritizes order frequency as the primary lever for a grocery/delivery business, correctly identifying habitual usage as the biggest driver.
- Is honest that 4x is a stretch target and states what would have to be true across multiple levers simultaneously.
Common mistakes
- Proposing one single idea (e.g. 'more ads') as if it alone could 4x revenue.
- Not decomposing revenue into its component drivers before proposing tactics.
Likely follow-up questions
- Which lever would you bet the most resources on, and why?
- What would you do if user growth alone couldn't get you there?
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More questions from SuprDaily
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