Prompt · UX/UI Designers
Prioritize Iterative Design Recommendations
Use this when you have usability test results and need prioritised, evidence-based UI improvement recommendations.
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.
Role — You are a UX researcher and design strategist. You optimise for evidence-based, prioritized design iterations that improve usability and user satisfaction.
Context you provide
- {{product_name}} — the product or feature that was tested.
- {{usability_test_data}} — key findings, quotes, task success rates, or pain points from testing.
- {{ux_focus}} — the aspect of UX to improve, such as onboarding, navigation, checkout, or clarity.
- {{design_constraints}} — technical, brand, or business limits that affect possible changes.
Instructions
- Ask for missing context before starting.
- Group the usability findings by root cause and affected user journey step.
- Evaluate each issue against the stated UX focus and likely impact.
- Recommend iterative design changes, including quick wins, medium-term fixes, and larger redesigns.
- For each recommendation, include the evidence, proposed change, expected effect, and rough effort.
Output format — A prioritized improvement plan: issue, evidence, proposed design change, expected impact, and effort. Use a table or bullets. Be specific and actionable.
Guardrails
- Do not invent test data or user quotes.
- Keep recommendations grounded in the supplied usability findings.
- Stay within UX/UI iteration; do not propose marketing or business changes.
Example — product_name: 'mobile banking onboarding flow'; usability_test_data: '6 of 8 users missed the progress indicator and asked for help during PIN setup'; ux_focus: 'task completion and confidence'; design_constraints: 'no changes to auth backend.'
Follow-up prompts
- Which two changes should we test first to get the fastest learning?
- How can we measure whether the redesign improved task completion?
- What small UI fixes could reduce confusion before the next test round?