jtbd-demand-mining

To identify real customer jobs behind a product request, map the functional, social, and emotional work users are trying to get done. This demand mining approach separates true underlying needs from solution-level requests through iterative why-based probing and severity ranking.

The best way to validate user needs during product discovery is by extracting pain points and expected gains, then categorizing them as true needs, partial needs, or not real needs. This structured output dictates what to validate next, separating must-have features from nice-to-haves.

To analyze root causes of customer churn using the jobs-to-be-done framework, perform iterative why-based probing to uncover the functional, social, and emotional work your product fails to support. This diagnoses whether users are mis-specified or misled by solution-level requests.

You should use JTBD demand mining when direct customer research yields solution-level requests that may mis-specify user needs. It applies when you need to reposition your market offering or validate requirements by diagnosing the deeper functional, social, and emotional motivations behind user feedback.

To start mapping functional, social, and emotional customer jobs, you need to define the step-by-step context, including your target user, the situation they are in, and what alternative solution they use today. This context anchors the iterative why-based probing process.