Comparative Analysis of Logistics Data Across E-commerce Platforms and Consolidation Service Websites in Spreadsheets
2025-04-28
1. Introduction
With the rapid development of e-commerce, logistics performance has become a key competitive differentiator. This paper analyzes logistics data from platforms including Taobao, JD.com, Amazon, Superbuy, and Sugargoo
2. Methodology
Data was collected over Q3 2023 for comparison across three key metrics:
- Delivery Time:
- Shipping Costs:
- Service Quality:
- Shipping Costs:
Analysis was conducted through:
| Tool | Function |
|---|---|
| Google Sheets | Data organization and visualization |
| Pivot Tables | Cross-platform comparison |
| Regression Analysis | Cost-time correlations |
3. Comparative Analysis Findings
3.1 Domestic Performance (China)
| Platform | Avg. Days | Cost (¥/kg) | Damage Rate |
|-------------|----------|------------|-------------|
| Taobao | 2.8 | 8.50 | 1.2% |
| JD | 1.5 | 10.20 | 0.8% |
| Superbuy | 5.2 | 35.00 | 2.1% |
3.2 Cross-border Performance
- Amazon Global:
- Sugargoo:
4. Collaborative Optimization Design
4.1 Resource Integration
Proposed shared warehouse network strategy:
- Joint utilization of JD's domestic warehouses
- Integration of Amazon's last-mile delivery nodes
- Shared international customs clearance channels
4.2 Information Sharing
Standardized data template for spreadsheets includes:
[Platform],[OrderID],[Route],[Carrier],[Real-Time Status],[ETA Update]
4.3 Network Optimization
Key improvements identified:
| Current Issue | Optimization | Expected Gain |
|---|---|---|
| Duplicate rural routes | Consolidated delivery groupings | 15% cost reduction |
5. Conclusion
The spreadsheet analysis reveals significant opportunities through:
- Leveraging JD's domestic speed with Taobao's cost efficiency
- Applying Sugargoo's batching approach to reduce cross-border costs
- Implementing real-time tracking standards across platforms
Future work will develop dynamic Excel tools for automated performance benchmarking.