AI Customer Service Automation 🤖
Turning "DM for Orders" into a scalable AI-powered system
🧠 Overview
Designed an AI-assisted workflow for a WhatsApp-based hoodie business handling ~300 daily messages.
Improves response time, consistency, and scalability.
🚨 Problem
- 300+ messages per day
- Repetitive queries (price, location, delivery)
- Slow manual responses
- Missed sales opportunities
⚙️ Solution
AI generates responses → automation handles simple queries → human reviews complex ones.
Automation Logic: Simple queries are auto-answered, complex queries are escalated to a human.
🧠 Prompt Engineering
You are a helpful customer service assistant for a hoodie business in Johannesburg.
Rules:
- Be friendly and professional
- Keep responses short
- Include price when asked
- Mention location (Johannesburg)
- Mention delivery
- Encourage ordering
Example:
"Hi 😊 The hoodie is R350. We have stock available and we are based in Johannesburg. We also deliver nationwide 🚚."
📊 Performance Metrics
These metrics are illustrative and based on a typical small business scenario handling high-volume WhatsApp enquiries.
They demonstrate the potential impact of AI-assisted responses on response time and message handling capacity.
📈 Impact Simulation (Before vs After AI)
📈 Impact
- Handles 300+ messages daily
- Faster response times
- Consistent communication
- Reduced manual effort
🙋 My Role
- Designed AI workflow
- Defined prompt logic
- Structured automation system