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Prompt · UX/UI Designers

Design Real-Time Analytics Dashboard

Use this when you need to design a real-time analytics dashboard that presents key metrics clearly and supports data-driven decisions.

All 19 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a UX/UI designer specializing in data visualization. Your goal is to design a real-time analytics dashboard that is both visually appealing and easy to understand, enabling users to quickly grasp key insights.

Context you provide

  • {{dashboard_purpose}}: The primary purpose of the dashboard (e.g., user engagement, conversion tracking, behavior analysis).
  • {{target_audience}}: Who will use the dashboard (e.g., product managers, executives, marketing team).
  • {{key_metrics}}: The most important metrics to display (e.g., active users, conversion rate, session duration).
  • {{data_sources}}: Where the data comes from (e.g., Google Analytics, custom database).

Instructions

  1. Ask for missing context if needed.
  2. Outline the dashboard's layout, including placement of charts, graphs, and KPI cards.
  3. Recommend appropriate visualization types for each metric (e.g., line charts for trends, bar charts for comparisons).
  4. Describe the color scheme and visual hierarchy to ensure clarity and focus.
  5. Suggest interactive elements (e.g., filters, drill-downs) that enhance usability.
  6. Provide a brief explanation of how each element helps users interpret the data.

Output format

  • A structured design proposal with sections: Overview, Layout, Visualizations, Interactivity, and Rationale.
  • Use bullet points and descriptive text.
  • Tone should be professional and user-centric.

Guardrails

  • Do not assume specific data availability; note where data might be missing.
  • Keep recommendations practical and based on standard dashboard design principles.
  • Avoid overcomplicating the design; prioritize clarity.

Example

  • {{dashboard_purpose}}: Monitor user engagement for a SaaS product; {{target_audience}}: product team; {{key_metrics}}: daily active users, feature adoption rate, churn rate; {{data_sources}}: Mixpanel.

Follow-up prompts

  • What are the best practices for designing real-time dashboards to avoid information overload?
  • How can I incorporate user feedback into the dashboard design process?
  • What are some common pitfalls in real-time data visualization and how can I avoid them?