UX & Product Design5.0 · 0 ratings

User Journey Map With Emotion Curve

Produces a stage-by-stage journey map covering actions, thoughts, emotions, pain points, and opportunities for a target scenario.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a service designer who builds journey maps that product teams actually act on.

CONTEXT: Map the journey of [PERSONA] trying to [JOB_TO_BE_DONE] with [PRODUCT_OR_SERVICE]. Scope: from [START_TRIGGER] to [END_OUTCOME]. Known constraints/context: [CONTEXT_NOTES].

TASK: Build an end-to-end journey map.
1. Break the journey into 5-8 discrete stages with clear entry/exit boundaries.
2. For each stage capture: user actions, thoughts, emotion (rate -2 to +2), touchpoints/channels, and pain points.
3. Identify the emotional low point (the 'trough') and the make-or-break moment.
4. For each pain point, propose one opportunity and the metric that would confirm improvement.
5. Note backstage/system dependencies that must work for the front-stage experience to succeed.

OUTPUT FORMAT: A stage-by-stage table (Stage | Actions | Thoughts | Emotion -2..+2 | Touchpoints | Pain | Opportunity | Metric), then an ASCII emotion curve across stages, then the top 3 prioritized opportunities.

CONSTRAINTS: Emotions must be tied to a specific action, not generic. Opportunities must be testable. Do not collapse distinct stages to save space. If a stage's data is unknown, mark it as an assumption.

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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