Diagnose a recent revenue decline at Flipkart's e-commerce marketplace

Quick Overview

A metric diagnosis question asking a product manager to find out why revenue has recently fallen at Flipkart, the Indian e-commerce marketplace. It tests defining revenue precisely, decomposing it into traffic, conversion, order value and take rate, localizing the drop, and ordering internal and external hypotheses.

Diagnose a recent revenue decline at Flipkart's e-commerce marketplace

Company: Walmart Labs

Role: Product Manager

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Other

You are a product manager at Flipkart, one of India's largest e-commerce marketplaces. Revenue metrics have fallen recently, and you are asked to find out why. Walk through how you would identify the cause. ```hint Decompose before you hypothesize Write revenue as a product of factors you can measure separately, then find which factor moved and where, before you start naming causes. ``` ### Clarifying Questions - Which revenue metric dropped: the value of goods sold on the platform, or Flipkart's own earnings from seller commissions, fees and advertising? - How large is the drop, over what period, and did it come suddenly or build gradually? - Is it broad, or concentrated in particular categories, regions, platforms (Android app, iOS app, mobile web) or customer groups? - Has anything changed recently on our side, such as an app release, a search or pricing change, a seller fee change, or a big sale event that falls in the comparison period? ### What a Strong Answer Covers - A precise definition of revenue for a marketplace and a decomposition into traffic, conversion, order value, take rate and advertising - Checking that the drop is real: data and tracking issues, seasonality, and sale events whose dates shift - Segmenting the drop to localize it before generating hypotheses - Internal and external hypotheses checked in a sensible order, each with the data that would confirm or rule it out - A conclusion: how to confirm the root cause, size its impact, and what to do next ### Follow-up Questions - Traffic and conversion are flat, but customers are putting fewer items in each order. Where do you look next? - The decline is concentrated in electronics and other high-priced items. Which hypotheses move to the top? - Every internal check comes back clean and competitors are growing. How would you test whether customers have shifted to a different way of shopping?

Overview: A metric diagnosis question asking a product manager to find out why revenue has recently fallen at Flipkart, the Indian e-commerce marketplace. It tests defining revenue precisely, decomposing it into traffic, conversion, order value and take rate, localizing the drop, and ordering internal and external hypotheses.

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Walmart Labs
Mar 26, 2026
mediumProduct ManagerOtherAnalytics & Experimentation
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You are a product manager at Flipkart, one of India's largest e-commerce marketplaces. Revenue metrics have fallen recently, and you are asked to find out why. Walk through how you would identify the cause.

Clarifying Questions Guidance

  • Which revenue metric dropped: the value of goods sold on the platform, or Flipkart's own earnings from seller commissions, fees and advertising?
  • How large is the drop, over what period, and did it come suddenly or build gradually?
  • Is it broad, or concentrated in particular categories, regions, platforms (Android app, iOS app, mobile web) or customer groups?
  • Has anything changed recently on our side, such as an app release, a search or pricing change, a seller fee change, or a big sale event that falls in the comparison period?

What a Strong Answer Covers Guidance

  • A precise definition of revenue for a marketplace and a decomposition into traffic, conversion, order value, take rate and advertising
  • Checking that the drop is real: data and tracking issues, seasonality, and sale events whose dates shift
  • Segmenting the drop to localize it before generating hypotheses
  • Internal and external hypotheses checked in a sensible order, each with the data that would confirm or rule it out
  • A conclusion: how to confirm the root cause, size its impact, and what to do next

Follow-up Questions Guidance

  • Traffic and conversion are flat, but customers are putting fewer items in each order. Where do you look next?
  • The decline is concentrated in electronics and other high-priced items. Which hypotheses move to the top?
  • Every internal check comes back clean and competitors are growing. How would you test whether customers have shifted to a different way of shopping?