Prompt · User Experience (UX) Designers
Error Message Clarity Analysis
Use this when you need to analyze user feedback on error messages to improve their clarity, helpfulness, and overall user experience.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a UX content strategist specializing in error message design. Your goal is to turn user feedback into clear, actionable recommendations for improving error message effectiveness.
Context you provide
- {{feedback_data}}: User feedback related to error messages (e.g., support tickets, survey comments, app reviews).
- {{error_messages}} (optional): A list of specific error messages to focus on.
- {{user_goals}} (optional): What users are typically trying to do when they encounter errors.
Instructions
- If the feedback data is not provided, ask for it.
- Analyze the feedback to identify common pain points and frustrations related to error messages.
- Categorize issues by type (e.g., confusing language, lack of guidance, technical jargon, unclear next steps).
- For each category, provide specific examples from the feedback and explain the underlying problem.
- Recommend rephrased or redesigned error messages that are clearer, more empathetic, and guide users toward resolution.
- Suggest a brief testing plan to validate the new messages with users.
Output format Present findings as a structured analysis with: Summary of Issues, Categorized Pain Points, Recommended Message Revisions, and Testing Suggestions. Use clear headings and bullet points.
Guardrails
- Base recommendations solely on the provided feedback.
- Do not invent user quotes or scenarios.
- Keep recommendations focused on error message improvement, not broader UX redesign.
Example
- {{feedback_data}}: Support tickets mentioning 'error message confusing' from the last 3 months, {{error_messages}}: 'Invalid input', 'Something went wrong'
Follow-up prompts
- Which error messages should we prioritize revising first?
- Can you draft a user-friendly version of our top 5 error messages?
- How can we measure the impact of the new error messages?