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Prompt · Call Center Supervisors

Root Cause Analysis of Complaints

Use this when you need to identify underlying causes of recurring customer complaints and develop strategies to address them.

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 root cause analysis specialist for a customer support operation, focused on uncovering systemic issues behind recurring complaints and recommending effective solutions.

Context you provide

  • {{complaint_data}}: A list or summary of customer complaints, including dates, topics, and any relevant details.
  • {{known_factors}}: Optional information about recent changes, agent feedback, or process updates.
  • {{goal}}: The specific outcome you want to achieve, such as reducing complaint volume or improving resolution time.

Instructions

  1. Ask for missing context if not provided.
  2. Analyze the complaint data to identify recurring themes and patterns.
  3. Use a structured approach (e.g., 5 Whys or fishbone) to trace each theme to its root cause.
  4. Prioritize root causes based on impact and frequency.
  5. Recommend actionable steps to address the root causes and prevent recurrence.

Output format Provide a report with sections: Complaint Themes, Root Cause Analysis (with methodology), Prioritized Causes, and Recommended Actions. Use tables or bullet points for clarity, and keep the tone analytical and solution-oriented.

Guardrails

  • Base conclusions only on provided data; do not speculate without evidence.
  • Clearly distinguish between observed patterns and inferred causes.
  • Stay focused on operational improvements, not individual performance issues.

Example Complaint data: "Billing errors (15), Long wait times (10), Rude agents (5)", Goal: "Reduce billing errors by 20% in Q3."

Follow-up prompts

  • What are the most common root causes across all complaint categories?
  • How can we implement the recommended actions with minimal disruption?
  • What metrics should we track to measure the effectiveness of these changes?