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Contextual Inquiry: Watch Users in Their Habitat

AI-drafted, machine-checkedSource: Wikipedia: Contextual inquiryintermediate

Go to the user's environment to see what they *actually* do, not just what they say they do. It's used in early discovery to uncover unstated needs by observing real workflows. The footgun is 'helping' the user, which pollutes the observation.

WHY IT EXISTS Users are often poor reporters of their own behavior. They forget steps, understate frustrations, and describe idealized workflows, not the messy reality. To build something truly useful, you need to see the real world. Contextual inquiry was created to bridge this gap between what people say and what they do.

THE MENTAL MODEL Think of it as a master-apprentice relationship. The user is the master of their work, and you are the apprentice, trying to learn it. You watch, ask clarifying questions, and build a shared understanding of their process, tools, and environment. You are there to observe and learn, not to teach, test, or sell.

HOW IT WORKS A researcher schedules a session, typically about two hours, with a user in their actual work environment. The researcher observes the user performing their normal tasks. The key is the ongoing conversation: the researcher asks questions like "Why did you do that?" or "What are you thinking right now?" to understand the user's intent and rationale in real-time. The researcher's role is to watch and probe, not to guide or correct.

WHEN TO USE IT Use this method at the very beginning of a project, before you've written a line of code. It's ideal for exploring a new domain, understanding complex existing workflows, or discovering unmet needs that could lead to innovative features or entirely new products. It generates rich, qualitative data about user motivations and environmental factors.

WHEN NOT TO USE IT Do not use contextual inquiry to evaluate a specific UI design or test a prototype's usability; that's what usability testing is for. It's also not a good method for getting statistically significant data, as the sample sizes are very small. It's an expensive, time-consuming method, so it's not practical for quick feedback cycles.

ONE CANONICAL EXAMPLE A team building new accounting software might conduct a contextual inquiry with an accountant during month-end closing. Instead of a survey, the researcher sits in the accountant's office, watching them use spreadsheets, old software, and paper binders. They'd see the accountant manually copy-pasting data between windows and using a calculator for quick checks—crucial pain points that would never show up in a formal interview.

Read the original → en.wikipedia.org

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