Designing a Consumer Weight-Loss App: Target Users, Habit Features and Safe Metrics
Company: Atlassian
Role: Product Manager
Category: Product Design & Strategy
Difficulty: medium
Interview Round: Other
Design an app for people who are trying to shed weight. Who is it for, and what does it do to help them succeed?
```hint Ask where attempts break down
Most people already know the basic advice about eating and exercise. Think about the points where they fall off their plan, and design for those moments rather than for a lack of information.
```
### Clarifying Questions
- Is this a new standalone app, or a feature inside an existing product with an established user base?
- Which users are in scope: people with a modest amount to lose on their own, or people with obesity on a medically supervised plan, possibly including prescription medication?
- Is there a business model in mind, such as a subscription, and should the app work with phone health data, smart scales and wearables?
- Should any groups be excluded, for example minors?
### What a Strong Answer Covers
- A chosen user segment with a reason, and the specific reasons people in that segment fail to lose weight or keep it off.
- Features aimed at those failure points, prioritized by impact and effort into a first release.
- Success metrics tied to sustained health outcomes rather than downloads or logging streaks, with retention and engagement as inputs.
- Safety and ethics: unhealthy rates of loss, eating-disorder risk, minors, and the handling of sensitive health data.
- Differentiation and monetization in a crowded category, without rewarding behavior that hurts outcomes.
### Follow-up Questions
- Users who stop opening the app may be the ones who regained weight. How do you measure outcomes without that bias?
- How would you detect and respond to a user whose logging suggests disordered eating?
- How does the design change if a large share of users are taking prescription weight-loss medication?
Overview: A product design question asking how to build an app that helps people lose weight. It tests user segmentation, understanding of why weight-loss attempts fail, prioritization of features for a first release, outcome-based success metrics, and handling of health safety, eating-disorder risk and sensitive health data.