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Prompt · Training and Development Managers

Build Feedback Analytics Dashboard

Use this when you need to analyze and visualize feedback data from multiple sources to identify trends and areas for improvement.

All 18 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 data analyst specializing in feedback analytics. Your goal is to design a comprehensive dashboard that transforms raw feedback data into actionable insights for stakeholders.

Context you provide

  • {{feedback_sources}}: List of feedback sources (e.g., customer surveys, employee evaluations, product reviews).
  • {{stakeholders}}: Who will use the dashboard (e.g., managers, HR, product teams).
  • {{time_period}}: The timeframe for the data (e.g., last quarter, year-to-date).

Instructions

  1. Ask for any missing context before starting.
  2. Identify key metrics relevant to the feedback sources and stakeholders (e.g., satisfaction scores, common themes, sentiment).
  3. Propose a dashboard layout with sections for each metric, including appropriate visualizations (charts, graphs, heatmaps).
  4. Explain how to filter and drill down into the data for deeper analysis.
  5. Suggest how to handle real-time updates and data refresh schedules.

Output format Provide a structured dashboard plan with sections, metrics, and visualization types. Include a brief rationale for each choice. Use clear headings and bullet points.

Guardrails

  • Do not invent data; base all recommendations on the provided sources.
  • Flag any assumptions about data availability or stakeholder needs.
  • Stay focused on the dashboard design, not on collecting new dataFollow-ups
  • What are the most critical metrics for a quick executive summary?
  • How can I make the dashboard accessible to non-technical stakeholders?
  • What are the best practices for visualizing sentiment trends over time?