Introduction
In the fast-paced world of reverse purchasing (代购), efficient after-sales service is critical to maintaining customer trust and platform reputation. This paper explores how digital spreadsheets can integrate with major purchasing platforms’ after-sales policies to streamline issue resolution, track progress, and enhance user satisfaction.
Common After-Sales Challenges
- Diverse policies across platforms (e.g., Taobao, Weidian, JD, Little Red Book)
- Language barriers in cross-border scenarios
- Time-sensitive refund/return windows
- Tracking communication across multiple channels
The Spreadsheet Solution Framework
Core Spreadsheet Functions:
Column |
Function |
Example |
Platform Policy |
Automatic policy summaries with dropdowns |
=VLOOKUP(Platform_Name, Policy_Database, 2, FALSE) |
Timeline Tracker |
Color-coded deadline alerts |
Conditional formatting for <48h windows |
Implementation Workflow:
- Centralized Case Logging:
Input all after-sales requests with key metadata (order ID, issue type, contact method)
- Policy Mapping:
Link to platform-specific flows (e.g., Taobao's 7-day no-reason returns vs. Pinduoduo's partial refunds)
- Automated Status Updates:
Scripts to pull the latest tracking info via API where available
Platform Policy Adaptations
Performance Analytics
Embedded pivot tables can reveal:
- Most common issue types (e.g., 42% sizing problems)
- Average resolution time per platform
- Customer satisfaction trends from feedback
Sample formula for SLA calculation: =AVERAGEIF(Resolution_Time_Range, "<72h")