Product design question
You are a product manager at T-mobile. Design a fridge for children. How will you estimate the market? How will you price the fridge? Should T-mobile invest in this business?
- T-Mobile
- Product design
- Hard
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What this question tests
Handling a deliberately odd, off-brand prompt with structured market sizing and an honest go or no-go recommendation.
How to approach it
- Flag the mismatch upfront: T-Mobile is a telecom carrier, not an appliance maker, so ask what strategic rationale would justify this, likely an IoT push.
- Define the product: a connected, kid-friendly fridge with parental-control, screen-time-style features, a plausible IoT angle for T-Mobile.
- Estimate the market top-down: roughly 30M US households with kids, times a low 1 to 2% attach rate for a niche connected appliance, as an assumption.
- Price using cost-plus and a comparable: connected mini-fridges retail around $150 to $300, so price near the top given smart features.
- Weigh whether to invest: compare this small, off-core opportunity against T-Mobile's core connectivity subscription business.
- Recommend likely passing or licensing the concept rather than manufacturing, since it's far from telecom's core competency and margins.
What a strong answer includes
- Names the mismatch honestly instead of pretending a telecom company obviously belongs in appliances.
- Shows explicit market-sizing math with assumptions clearly marked as assumptions.
- Reaches a clear recommendation, likely no or partner and license, rather than dodging the ask.
Common mistakes
- Diving into fridge feature design without ever questioning why T-Mobile would do this.
- Giving no market-sizing numbers when explicitly asked to estimate.
Likely follow-up questions
- What connectivity angle would make this actually make sense for T-Mobile?
- How would you test demand before committing capital?
More product design questions
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More questions from T-Mobile
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop