Rank Homepage Modules for an E-Commerce Product

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Quick Overview

Rank e-commerce homepage modules using business objectives, seasonal eligibility, slot effects, slate diversity, cold-start exploration, and page-level experiments.

Rank Homepage Modules for an E-Commerce Product

Company: Wayfair

Role: Applied Scientist

Category: ML System Design

Difficulty: medium

Interview Round: Onsite

Design a ranking system for modules on an e-commerce homepage. Candidate modules include trending products and seasonal or holiday sales. Focus on the product goal and the business consequences of the ranking, then explain the modeling and serving approach. ### Constraints & Assumptions A module is a block of content, not a single product. The report does not fix the number of slots, candidate-generation rules, or objective. State those assumptions and distinguish ranking modules from ranking the items inside each module. ### Clarifying Questions Which user outcomes matter? Are some modules contractual or mandatory? How fresh must trending and holiday content be? Can several modules show overlapping products? ### What a Strong Answer Covers Define candidate eligibility, contextual value, slot effects, diversity and overlap constraints, and an experiment that captures the effect on the whole homepage. ### Follow-up Questions How would you rank for a new visitor, evaluate a new holiday module without historical clicks, and avoid showing several nearly identical modules? What would you do if clicks rise but purchases or user satisfaction fall?

Overview: Rank e-commerce homepage modules using business objectives, seasonal eligibility, slot effects, slate diversity, cold-start exploration, and page-level experiments.

Read the full Wayfair Applied Scientist interview experience this question came from

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Wayfair
Sep 10, 2026
mediumApplied ScientistOnsiteML System Design
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Design a ranking system for modules on an e-commerce homepage. Candidate modules include trending products and seasonal or holiday sales. Focus on the product goal and the business consequences of the ranking, then explain the modeling and serving approach.

Constraints & Assumptions

A module is a block of content, not a single product. The report does not fix the number of slots, candidate-generation rules, or objective. State those assumptions and distinguish ranking modules from ranking the items inside each module.

Clarifying Questions Guidance

Which user outcomes matter? Are some modules contractual or mandatory? How fresh must trending and holiday content be? Can several modules show overlapping products?

What a Strong Answer Covers Guidance

Define candidate eligibility, contextual value, slot effects, diversity and overlap constraints, and an experiment that captures the effect on the whole homepage.

Follow-up Questions Guidance

How would you rank for a new visitor, evaluate a new holiday module without historical clicks, and avoid showing several nearly identical modules? What would you do if clicks rise but purchases or user satisfaction fall?

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