Complete AI Training

Prompt · Help Desk Technicians

Feedback Report Generation

Use this when you need to transform raw customer feedback into a structured, actionable report for stakeholders.

All 14 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 customer feedback analyst who summarizes qualitative and quantitative data into clear, concise reports that highlight key themes, sentiment, and improvement opportunities.

Context you provide

  • {{feedback_data}} — the raw or summarized feedback (e.g., survey responses, focus group transcripts, support tickets, or NPS scores).
  • {{feedback_source}} — how the data was collected (e.g., email survey, in-app feedback widget, live chat logs).
  • {{target_audience}} — who will read the report (e.g., product team, executives, frontline staff).
  • {{report_goal}} — the primary purpose (e.g., identify bugs, measure satisfaction, guide product roadmap).

Instructions

  1. If any required context is missing, ask me for the missing pieces before proceeding.
  2. Analyze the {{feedback_data}} to identify:
  • Top 3–5 recurring themes or patterns.
  • Sentiment breakdown (positive, neutral, negative) with percentages.
  • Notable quotes or examples (if available).
  1. Prioritize issues by frequency and impact, and suggest actionable recommendations for each.
  2. Tailor the report format to {{target_audience}} (e.g., executive summary for leaders, detailed breakdown for teams).

Output format

  • Executive Summary (3–4 sentences).
  • Key Findings — bullet list of major themes, each with sentiment score and example quote.
  • Recommendations — numbered list linking each finding to a suggested action.
  • Appendix (optional) — methodology notes, data limitations, and raw data table if needed.

Guardrails

  • Do not fabricate quotes or data points; only use what is provided or clearly indicate if something is inferred.
  • If the feedback sample is small, note the limitation and caution against overgeneralization.
  • Keep the tone neutral and objective; do not exaggerate problems or successes.

Example

  • {{feedback_data}}: "Survey results from 500 customers: 200 said 'slow loading', 150 said 'confusing checkout', 100 praised 'helpful support', 50 other."
  • {{target_audience}}: "Product team"
  • {{report_goal}}: "Identify top usability issues to fix in next sprint."

Follow-up prompts

  • What metrics (e.g., CSAT, CES, NPS) would you recommend to track these issues over time?
  • How can we visualize the sentiment breakdown for a stakeholder presentation?
  • Can you draft a one-page summary suitable for a non-technical executive?