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Taobao / Pinduoduo Store Owner

E-Commerce Support: 10 People Down to 3

A Taobao store's customer service automation story

Client Profile

Running a women's clothing store, peak season monthly revenue of 400-600K RMB, handling 150-300 daily inquiries

10 down to 3
Support Team
85% auto-resolved
Common Questions
From 5 min to under 30s
Avg Response
Handled 5x volume
Double 11

The Challenge

Had 10 support staff with salaries eating up a big chunk of revenue. The worst part was the sheer volume of repetitive questions — 'Do you have this in XL?' 'Where's my package?' 'Can I return this?' — easily half of all inquiries. Night shift was the hardest to staff, and customers waiting for responses would leave bad reviews. During Double 11, inquiries exploded and there was no time to hire and train temps.

The Solution

Built a support Agent system. First, we used six months of her chat history and FAQ documents to create a knowledge base. Then trained an auto-reply Agent to handle common questions. More complex cases like return disputes or quality complaints get routed to human agents automatically, along with the full chat history and order details so the agent doesn't have to ask the customer again. Added a weekly report Agent that tracks response times, top 10 common issues, and satisfaction trends — delivered to Feishu every Monday.

Technical Architecture

Taobao/Pinduoduo Message API
Intent Recognition
Knowledge Base Match
Common Question Auto-Reply / Complex Issue Routing (with history)
Human Agent
Data Aggregation
Weekly Report

Execution Flow

1
Buyer message intake
2
Intent and sentiment detection
3
Knowledge base matching
4
Unresolved cases routed to humans
5
Human after-sales processing
6
Weekly report auto-generation

During Double 11, inquiries jumped 5x. The Agent handled sizing questions and shipping lookups while I only dealt with returns and complaints. Lifesaver.

X
Xiao Min
Taobao / Pinduoduo Store Owner

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