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I had a story ready but partway through I realized I was describing a situation where I kind of just guessed and got lucky, which is not a great look.
Use the STAR method to describe a specific situation where you initially misunderstood customer needs, then explain how you adapted your approach to uncover the real problem. Emphasize the engineering mindset: iterative discovery, data-driven validation, and cross-functional collaboration to deliver the right solution.
Pro tip: Show that you treat customer needs as hypotheses to be validated, not assumptions to be built upon. Highlight how you used lightweight prototypes or user feedback loops to converge on the right solution quickly.
Briefly describe the customer, product area, and why the need was ambiguous. Mention any initial assumptions you or the team had.
Explain the specific challenges in understanding the customer's true needs, such as conflicting requirements, technical jargon, or missing information.
Detail the steps you took to uncover the real need, such as conducting user interviews, analyzing usage data, or building a prototype to elicit feedback.
Share the resulting product or service recommendation and its impact, using metrics if possible (e.g., increased adoption, reduced support tickets).
Summarize what you learned about eliciting customer needs and how you've applied that lesson to subsequent projects.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.