AI-Powered Customer Service for E-Commerce Retailer
Building an intelligent support system that handles 80% of customer enquiries automatically while improving satisfaction scores.
Key Results
80% of enquiries automated
45% improvement in response time
NPS increased from 42 to 67
The Challenge
StyleHouse, a fast-growing Australian fashion e-commerce brand, was struggling to scale their customer support. With order volumes growing 40% year-over-year, their support team was overwhelmed:
- Average response time had blown out to 18 hours
- Simple queries (order status, returns process) consumed 70% of agent time
- Peak periods (sales, holidays) created massive backlogs
- Agent turnover was high due to repetitive work
They needed a solution that could handle volume without sacrificing the personal touch their brand was known for.
Our Approach
We built an AI-powered support system that goes far beyond simple chatbots:
Intelligent Triage
Every incoming enquiry is analysed for:
- Intent classification — What does the customer actually want?
- Sentiment detection — Are they frustrated, confused, or just asking a question?
- Urgency assessment — Does this need immediate attention?
- Complexity scoring — Can AI handle this, or should it go to a human?
Contextual Understanding
The AI agent has access to:
- Complete order history
- Previous support interactions
- Product information and inventory
- Shipping and logistics data
- Return and refund policies
This means it can answer questions like "Where's my order?" with a specific, personalised response — not a generic tracking link.
Seamless Handoff
When an enquiry requires human intervention:
- Complete context is passed to the agent
- Customer doesn't need to repeat themselves
- AI suggests responses based on similar past tickets
- Human can override or approve AI suggestions
Technical Implementation
Architecture overview:
Incoming Query
↓
Intent Classification (Claude)
↓
Context Retrieval (RAG)
↓
Response Generation (GPT-4)
↓
Confidence Check
↓
[High Confidence] → Auto-respond
[Low Confidence] → Human Review
Key integrations:
- Shopify for order and product data
- Gorgias for ticket management
- Slack for internal escalations
- Custom dashboard for monitoring and training
Results
After 6 months:
| Metric | Before | After | |--------|--------|-------| | First response time | 18 hours | 2 minutes | | Resolution time | 36 hours | 4 hours | | Tickets handled by AI | 0% | 80% | | Agent productivity | Baseline | +120% | | NPS Score | 42 | 67 | | Support cost/order | $2.40 | $0.85 |
The Human Element
Crucially, this isn't about replacing humans — it's about augmenting them:
- Agents now focus on complex, high-value interactions
- They have AI-assisted tools that make their jobs easier
- Customer satisfaction has improved for both AI and human interactions
- The team has grown (not shrunk) as the business scales
Continuous Improvement
The system gets smarter over time:
- Feedback loops — Agent corrections train the model
- A/B testing — We continuously test response variations
- Edge case capture — New scenarios are flagged and addressed
- Performance monitoring — Real-time accuracy and satisfaction tracking
StyleHouse now has a support system that scales with their growth, maintains their brand voice, and actually improves customer experience.
“Our customers can't tell they're talking to an AI, and frankly, they don't care — they just want fast, accurate answers. That's exactly what we deliver now.”