Why Conduct a Yearly Data Review?
Scrolling through countless orders only gives you fragments of the story. A consolidated yearly review of your LoveGoBuy agent data transforms these fragments into actionable shopping intelligence. By summarizing your orders, refunds, and Quality Control (QC) performance, you can:
- Quantify Shopping Efficiency:
- Identify Trusted Sellers Systematically:
- Spot Costly Patterns:
- Optimize Future Budgets:
Step-by-Step: Mining Your Spreadsheet for Insights
Your LoveGoBuy order spreadsheet is a goldmine. Here’s how to pan for gold.
Step 1: Summarize Total Orders & Spending
Create a pivot table or sort your data to find:
- Total Number of Orders:
- Total Amount Spent (in CNY/USD):
- Average Order Value:
Step 2: Analyze Refund & Exchange Data
This is crucial for measuring risk. Filter or create a separate sheet for items marked "Refunded" or "Exchanged." Calculate:
- Refund/Exchange Rate:
- Total Money Recovered:
- Common Refund Reasons:
Step 3: Evaluate QC Photo Performance
Your agent’s QC photos are your first line of defense. Review:
- QC-Flagged Items:your agent's
- Your Personal QC Pass Rate:you
- This helps assess both product accuracy and your own scrutiny level.
Step 4: Identify Your Trusted Sellers
This is the most valuable output. Create a "Trusted Seller List"
- High Volume Purchases:
- Perfect or Near-Perfect Record:
- Consistent QC Results:
Conversely, flag sellers with high refund rates for avoidance.
Bringing It All Together: Your Annual Shopping Report
Compile your findings into a simple one-page summary. For example:
| Metric | 2024 Data | Insight & Action |
|---|---|---|
| Total Orders | 47 | Steady pace; ~4 hauls per month. |
| Total Spent (CNY) | 8,450 CNY | Budget slightly exceeded. Set a firm 2025 limit. |
| Refund Rate | 12% (6 of 50 items) | High.Action: |
| Top Trusted Seller | Seller "TopStoney" | 8 orders, 0 refunds. Action: |
| Seller to Avoid | Seller "AAA-Jeans" | 3 orders, 3 refunds (quality issues). Action: |