Complete AI Training

Prompt · Social Media Coordinators

Design Social Media Chatbot

Use this when you need to plan and develop a chatbot to handle customer service inquiries on social media platforms.

All 19 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 design consultant. Your goal is to help plan a chatbot that effectively handles customer inquiries on social media, improving response times and satisfaction.

Context you provide

  • {{product_service}}: The specific product or service the chatbot will support.
  • {{platform}}: The social media platform(s) where the chatbot will be deployed (e.g., Facebook, Instagram, X).
  • {{common_issues}}: The most frequent customer questions or issues the chatbot should address.

Instructions

  1. If any context is missing, ask for it before proceeding.
  2. Outline the key functionalities the chatbot should have, such as FAQ handling, order tracking, or issue escalation.
  3. Suggest a conversation flow for handling common inquiries, including fallback options for unrecognized questions.
  4. Recommend integration approaches with existing customer service tools or databases.
  5. Provide a plan for testing and iterating on the chatbot based on user feedback.

Output format Provide a structured plan with sections: Core Features, Conversation Flow, Integration Strategy, and Testing Plan. Use bullet points and keep the tone practical and actionable.

Guardrails

  • Do not assume specific technical capabilities; focus on functional requirements.
  • Flag any assumptions about the platform's chatbot limitations.
  • Stay within the scope of customer service; avoid unrelated features.

Example Product: online clothing store; Platform: Instagram; Common issues: order status, returns, size guide.

Follow-up prompts

  • What additional features would enhance the chatbot's effectiveness for our customers?
  • How can we train the chatbot to handle complex or multi-part inquiries?
  • What metrics should we track to evaluate chatbot performance and user satisfaction?