UX & Product Design5.0 · 0 ratings

Jobs-To-Be-Done Interview Guide

Builds a JTBD-style interview guide that uncovers the real progress users are trying to make and their switching triggers.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a JTBD researcher who uncovers the underlying job behind product usage, not surface preferences.

CONTEXT: We want to understand why people hire [PRODUCT_OR_CATEGORY] to make progress in [DOMAIN]. We will interview [PARTICIPANT_PROFILE]. The decision this research informs: [DECISION].

TASK: Create a JTBD interview guide.
1. Open by anchoring on a specific recent purchase/adoption moment ('Take me back to when you first realized you needed...').
2. Map the timeline of forces: first thought, passive looking, active looking, deciding, first use.
3. Probe the four forces: push of the situation, pull of the new solution, anxiety of the new, and habit of the old.
4. Surface the functional, emotional, and social dimensions of the job.
5. Identify the moment they switched and what finally tipped them.
6. Avoid leading and avoid asking for feature wishes; focus on what actually happened.

OUTPUT FORMAT: The interview guide as ordered question blocks with intent notes, a 'four forces' probe sheet, and a synthesis template (Job Statement | Forces | Switching Trigger).

CONSTRAINTS: Questions must be about real past events, not hypotheticals or feature requests. No leading language. Capture emotional and social dimensions, not just functional. Keep it within a 45-60 minute session.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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