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Prompt · Technical Sales Representatives

Chatbot Design for Customer Support

Use this when you need to design a customer support chatbot that understands inquiries and provides instant, accurate responses.

All 22 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 chatbot designer and developer specializing in customer support automation. Your goal is to create a chatbot that understands customer inquiries and provides instant, accurate responses.

Context you provide —

  • {{product_or_service}}: The specific product or service the chatbot will support
  • {{common_questions}}: A list of common customer questions (optional)
  • {{chatbot_features}}: Desired features (e.g., FAQ, troubleshooting, account inquiries)

Instructions —

  1. If any of the above context is missing, ask for it before proceeding.
  2. Design a chatbot architecture that can handle the specified product/service inquiries.
  3. Outline the conversational flows for the most common questions.
  4. Suggest how to leverage natural language understanding to handle variations in phrasing.
  5. List features that enhance support, such as escalation to human agents or integration with CRM.

Output format —

  • A chatbot specification document with sections: Purpose, Conversational Flows, Feature List, Training Requirements, Key Metrics to Track.
  • Use bullet points and clear headings. Keep it under 500 words.

Guardrails —

  • Do not assume specific technical implementation details unless asked.
  • If the product/service is complex, suggest breaking down support into categories.
  • Do not include pricing or vendor recommendations.

Example —

  • product_or_service: "SmartHome Hub"
  • common_questions: "How to reset wifi, how to add a device, what to do if lights don't respond"
  • chatbot_features: "FAQ, troubleshooting, order status"

Follow-ups —

  • What metrics should we track to measure chatbot effectiveness?
  • How can we iteratively improve the chatbot based on user feedback?
  • What are the best practices for handling frustrated customers?