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Customer interviews are a structured qualitative method for gathering direct user feedback about needs, behaviours, and motivations. Conducted early in discovery, they inform product assumptions, prioritize features, and expose unmet user needs. They require careful question design, recruitment strategy, and ethical handling of participant data.
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A customer interview is a structured qualitative interview method used to understand customer needs, behaviors, and motivations and to test assumptions during discovery.
The method grew out of user research and UX practice as teams needed a reliable way to learn, before building, who users are, what they try to achieve, and why existing solutions fail. Customer interviews combine qualitative conversation, iterative discovery, and ethical data handling; they are used to check assumptions and surface unmet needs before observation or usability tests examine actual use.
A good interview is neither an interrogation nor a questionnaire, but a guided path to insight: first define what you want to learn. Then recruit suitable participants and use a flexible guide to ask open-ended questions. Follow-up prompts deepen the answers, patterns are later condensed, and the findings are compared with other methods.
Customer interviews are a method within user research and provide qualitative insight for product and design decisions.
An interview needs concrete learning questions; without them, conversations stay too broad to analyze well.
A guide sets topics, sequence, and possible follow-up prompts without making the session rigid.
Questions about experiences, motives, and situations produce richer answers than yes/no wording.
Follow-up prompts clarify examples, reasons, and meaning instead of collecting only the first answer.
Suitable participants and careful data handling reduce bias and protect the people involved.
Customer interviews are especially useful in discovery, problem framing, audience definition, feature prioritization, or before a redesign. They provide language, motives, and context, but they do not measure frequency or prove real-world usability; for that, use observation, testing, or quantitative data as well. Their quality depends heavily on sampling, question design, and interviewing skill.
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