Product design question
ChatGPT wants to add shopping. How would you choose the first user segment and shopping use case, define the product vision, and scope an MVP that helps users discover, compare, and confidently buy products while preserving trust?
- OpenAI
- Product design
- Hard
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What this question tests
Tests product vision and MVP scoping for a brand new shopping capability, balancing user trust against commercial goals from the start.
How to approach it
- Choose a first user segment with clear, high intent shopping needs and lower risk tolerance requirements, such as users already asking ChatGPT for product comparisons.
- Choose a first use case, likely product discovery and comparison for a specific category, rather than full transactional checkout across all categories.
- Define the MVP to help users discover and compare confidently, deferring full purchase completion in app if trust and merchant integration are not yet mature.
- Bake trust into the MVP from the start: transparent sourcing of recommendations, clear disclosure of any sponsored placement, and no pressure tactics.
- Scope cuts explicitly: defer personalization based on purchase history and defer complex categories like large appliances that need more research depth.
- Define success for the MVP as decision confidence and follow through, not just click through to a retailer, since trust is the core risk here.
What a strong answer includes
- Chooses a narrower first use case, discovery and comparison, over full transactional checkout, correctly sequencing trust building before commerce completion.
- Bakes transparency and disclosure into the MVP itself rather than treating it as a later trust patch, given how easily shopping recommendations can feel pushy.
- Defines success around decision confidence rather than raw click through, which better reflects the actual user and trust goal at this early stage.
Common mistakes
- Scoping the MVP around full transactional checkout across many categories before trust and merchant integration are proven.
- Measuring success purely by click through or conversion without checking whether users actually trusted the recommendation.
Likely follow-up questions
- How would you decide which product category to launch first?
- What would you do if early engagement is strong but users report the recommendations feel too promotional?
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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