Analysis and Optimization of Hoobuy's Proxy Purchase Logistics Costs in Spreadsheets
2025-04-24
1. Introduction
In the competitive world of cross-border proxy purchasing, logistics cost efficiency directly impacts profitability. This article demonstrates how Hoobuy can leverage spreadsheet analysis to optimize shipping combinations by evaluating key variables including:
- Carrier-specific freight rates by weight/volume tiers
- Insurance fee structures
- Regional tariff variations
- Delivery time SLA benchmarks
2. Data Structuring Methodology
2.1 Core Data Tables
| Logistics Channel | Weight Tier (kg) | Base Freight ($) | Volume Rate ($/m³) | Insurance (% of value) | Avg. Transit Days |
|---|---|---|---|---|---|
| Express A | 0-2 | 15.00 | 25.00 | 1.2% | 5 |
| Express B | 2-5 | 22.50 | 18.00 | 0.8% | 7 |
2.2 Dynamic Calculation Fields
=INDEX(carrier_rates, MATCH(volume,vol_tiers,1),3) + (declared_value*insurance_rate)
3. Optimization Framework
Constraints:
- Maximum acceptable delivery time ≤ 10 days
- Item value ≤ $200 requiring insurance
- 48-hour consolidated packaging window
Decision Variables:
- Carrier selection matrix
- Shipment consolidation threshold
- Insurance inclusion criteria
3.1 Scenario Analysis Tools
Implement Conditional Formatting
Example: Green highlight when (Cost ≤ $25 AND Days ≤ 8)
4. Implementation Case Study
4.1 Sample Item
- Product:
- Properties:
4.2 Carrier Comparison (USD)
| Option | Freight | Insurance | Surcharges | Total | Days |
|---|---|---|---|---|---|
| Express A | 15.00 | 2.16 | 3.00 | 20.16 | 5 |
| Standard C | 12.50 | 2.16 | 6.25 | 20.91 | 8 |