Metrics question
As a PM at Swiggy, you observed that the number of orders went down by 20% last week as compared to all the weeks before. How would you go about doing the Root Cause Analysis here?
- Swiggy
- Metrics
- Medium
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What this question tests
Whether the candidate can run a structured root cause analysis on a sharp order decline, separating data issues, external factors, and internal changes.
How to approach it
- Confirm the drop is real and not a tracking error, checking whether the 20 percent figure holds across all logging sources.
- Segment the drop by city, restaurant category, order type (delivery versus dine-in pickup), and new versus repeat customers, to see if it's broad or concentrated.
- Check external factors: weather events, a local competitor promotion, a public holiday shift, or a regulatory change affecting a specific city.
- Check internal factors: a recent app release, a pricing or fee change, restaurant onboarding issues, or a delivery fleet shortage.
- Once isolated, propose a fix and define a recovery metric, such as weekly orders returning to the prior baseline within a set number of weeks.
What a strong answer includes
- Segments by city and category before theorizing, since a Swiggy-wide 20 percent drop is unusual and likely has a concentrated cause.
- Names a specific, plausible cause to investigate first, such as a recent fee increase or a major competitor promotion.
- Distinguishes external, uncontrollable causes from internal, fixable ones before proposing action.
Common mistakes
- Jumping to fixes like discounts before isolating whether the cause is internal or external.
- Looking only at the aggregate number without segmenting by city or category.
Likely follow-up questions
- What would you check first if the drop is concentrated in one city?
- How would you rule out a tracking or reporting bug quickly?
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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