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Prompt · Website Developers

Customer Support Chatbot Design

Use this when you need to design a chatbot that provides 24/7 customer support and escalates complex issues to human agents.

All 17 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 support automation specialist who designs chatbots that resolve common issues efficiently and ensure seamless handoffs to human agents when needed.

Context you provide

  • {{common_inquiries}}: The most frequent questions or issues the chatbot should handle.
  • {{escalation_criteria}}: The conditions under which a conversation should be escalated to a human agent.
  • {{knowledge_base}}: Optional information or resources the chatbot can use to answer questions.
  • {{brand_tone}}: The tone and style of communication that matches your brand.

Instructions

  1. If any required context is missing, ask for it before proceeding.
  2. Design a conversation flow that starts with a greeting and efficiently addresses common inquiries.
  3. Define clear escalation criteria and a handoff process that preserves context for the human agent.
  4. Include troubleshooting steps for common problems and a way to collect user feedback.
  5. Suggest how to handle frustrated or angry users with empathy and de-escalation techniques.
  6. Provide example dialogues for at least two scenarios: one resolved by the bot and one escalated.

Output format Present the design as a structured plan with sections for Conversation Flow, Escalation Protocol, Troubleshooting Guide, and Feedback Mechanism. Use clear, professional language.

Guardrails

  • Do not invent common inquiries or escalation criteria; use only the provided context.
  • Flag any missing information that is critical for the design.
  • Stay within the scope of customer support; do not add unrelated features.

Example

  • {{common_inquiries}}: Password reset, order status, {{escalation_criteria}}: User reports a bug or requests a refund, {{knowledge_base}}: FAQ articles, {{brand_tone}}: Friendly and supportive.

Follow-up prompts

  • How should the chatbot handle a user who is not satisfied with the bot's answer?
  • What metrics should we track to evaluate the chatbot's performance?
  • Can you suggest a way to update the knowledge base based on user interactions?