Skip to content
Back to challenges
Metrics-first Product ModelingOpen Scenarioadvanced35 min

Marketplace activation drop

Practice turning a product metric drop into clarifying questions, metrics, grain choices, and tradeoff communication.

How this preview works
Preview this problem before signing in. Sign in to save progress and submit work.

Concept

fact-table-grain

The primary modeling idea this problem reinforces.

Requirements

4

Business needs the model must satisfy.

Read the concept guide: Fact table grain
Scenario

A marketplace team says listing activation dropped after a seller onboarding change. The interviewer asks you to define the metrics, design the model, and explain how you would debug whether the drop came from seller mix, category changes, listing quality, or purchase conversion.

Why this matters

This is the bridge from guided concept practice to interview mode. The schema matters, but the verdict depends on whether the candidate clarifies the product question, defends grain, and explains tradeoffs.

Requirements
  • Define listing activation numerator, denominator, time window, and exclusions.
  • Propose facts and dimensions that support activation, purchase conversion, seller mix, and category breakdowns.
  • State where seller or category history matters and how the model preserves it.
  • Explain at least one simpler alternative and when it would be acceptable.
Analytical goals
  • Define listing activation and purchase conversion metrics before schema design.
  • Separate listing lifecycle events from purchase conversion facts.
  • Explain seller/category history choices and production debugging concerns.

Try the question first.

The discussion has other people's approaches and solutions. Give it a real attempt before you read them.