Apparel Store Product Design: AI Help for Shoppers Choosing and Trying On Clothes

Quick Overview

A product design question about building an AI-powered application that helps shoppers in a physical clothing store check out garments and try them on. It tests choosing a shopper segment, finding pain points in the in-store journey, deciding where AI genuinely helps, prioritizing a first release, and defining metrics and privacy safeguards.

Apparel Store Product Design: AI Help for Shoppers Choosing and Trying On Clothes

Company: Salesforce

Role: Product Manager

Category: Product Design & Strategy

Difficulty: medium

Interview Round: Other

You are the product manager for an AI-powered application that a store will offer its shoppers, meant to help them check out clothes and try them on while they are in the store. Design the product: decide whom it serves and which problem it tackles first, describe the experience, show where AI does something a plain app or a store associate cannot, prioritize a first release, and explain how you would measure success. ```hint Follow one visit Trace a single shopper from walking in to leaving, with or without a purchase, and mark each point where they stall or give up; then ask which of those points needs a prediction or a recognition step rather than just more information. ``` ### Clarifying Questions - Is this for one retailer's own stores, or a product offered to many retailers with different catalogs and store layouts? - Does "checking out" clothes mean browsing and judging them, or should the application also take payment? - Where does it run: on the shopper's phone, on a screen or mirror in the fitting room, or on a device carried by store staff? - Which outcome matters most to the retailer: more purchases per visit, larger baskets, fewer returns, or shopper satisfaction? ### What a Strong Answer Covers - A goal for the application and how it serves both shoppers and the retailer - A chosen shopper segment and the reasons for choosing it - Pain points across the in-store journey, from finding items to the fitting room, ranked by severity - Solutions where AI is essential rather than decorative, prioritized into a first release, with the form factor justified - Success metrics with guardrails, plus risks such as privacy, recommendation accuracy and store-staff adoption ### Follow-up Questions - How would you get shoppers to share body measurements or photos, and what would you do if most of them refuse? - How would you show that the application increases sales, rather than simply being used by people who would have bought anyway? - If the retailer's store inventory data were only refreshed overnight, how would your design change?

Overview: A product design question about building an AI-powered application that helps shoppers in a physical clothing store check out garments and try them on. It tests choosing a shopper segment, finding pain points in the in-store journey, deciding where AI genuinely helps, prioritizing a first release, and defining metrics and privacy safeguards.

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Salesforce
Apr 12, 2024
mediumProduct ManagerOtherProduct Design & Strategy
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You are the product manager for an AI-powered application that a store will offer its shoppers, meant to help them check out clothes and try them on while they are in the store. Design the product: decide whom it serves and which problem it tackles first, describe the experience, show where AI does something a plain app or a store associate cannot, prioritize a first release, and explain how you would measure success.

Clarifying Questions Guidance

  • Is this for one retailer's own stores, or a product offered to many retailers with different catalogs and store layouts?
  • Does "checking out" clothes mean browsing and judging them, or should the application also take payment?
  • Where does it run: on the shopper's phone, on a screen or mirror in the fitting room, or on a device carried by store staff?
  • Which outcome matters most to the retailer: more purchases per visit, larger baskets, fewer returns, or shopper satisfaction?

What a Strong Answer Covers Guidance

  • A goal for the application and how it serves both shoppers and the retailer
  • A chosen shopper segment and the reasons for choosing it
  • Pain points across the in-store journey, from finding items to the fitting room, ranked by severity
  • Solutions where AI is essential rather than decorative, prioritized into a first release, with the form factor justified
  • Success metrics with guardrails, plus risks such as privacy, recommendation accuracy and store-staff adoption

Follow-up Questions Guidance

  • How would you get shoppers to share body measurements or photos, and what would you do if most of them refuse?
  • How would you show that the application increases sales, rather than simply being used by people who would have bought anyway?
  • If the retailer's store inventory data were only refreshed overnight, how would your design change?