Advocate for generative research over a complex feature request?
Tests mapping research methods to product risk. Strong answers reframe the feature as an unvalidated problem, cite qualitative behavioral methods like field studies, and translate unknowns into scope and opportunity cost.
Tests whether you can align generative research with engineering risk mitigation. A strong answer reframes the single request as an attitudinal data point requiring behavioral validation, then advocates for qualitative contextual methods such as field studies to map the actual problem space. It explicitly ties research to technical unknowns including integration surface area, data model assumptions, migration paths, and opportunity cost.
Read the original → nngroup.com
- #ux research
- #generative research
- #stakeholder management
- #product strategy
- #nngroup
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