Step 1: Filter for Consistent High QC Scores
Apply a filter to the "QC Pass Rate (%)"95%). This instantly isolates sellers who consistently deliver quality.
OrientDig: Evaluating Seller Performance Trends Using Spreadsheet Analytics
2026-02-03
Effectively monitoring seller performance is crucial for maintaining quality and customer satisfaction on platforms like OrientDig. A well-organized spreadsheet, with the right metrics and filters, can transform raw data into actionable insights. This guide walks you through the process.
Core Metrics for Evaluation
Focus on these three critical data points to build a comprehensive view of seller performance:
- QC Results (Quality Control Pass Rate):
- Rejection Rates:
- Refund Frequency:
- Rejection Rates:
Structuring Your OrientDig Spreadsheet
Organize your data with clear columns. A typical setup might include:
| Seller ID | Seller Name | QC Pass Rate (%) | Monthly Rejection Rate (%) | Refund Frequency (%) | Total Orders (Period) | Performance Tier |
|---|---|---|---|---|---|---|
| OD-S102 | PrimeGoods Co. | 98.5 | 1.2 | 0.8 | 500 | Excellent |
Step-by-Step Analysis with Filters
Step 2: Identify Low Rejection Rates
Next, filter the "Monthly Rejection Rate (%)"
Step 3: Analyze Refund Frequency for Customer Satisfaction
Finally, filter the "Refund Frequency (%)"
Step 4: Spot Negative Trends
Reverse the process. Filter for declining QC scoresrising rejection/refund rates
Turning Insights into Action
By systematically applying these simple spreadsheet filters to your OrientDig seller data, you can move from intuition to data-driven decision making. Regularly update your dataset and repeat this analysis to:
- Reward & Incentivize:
- Improve Collaboration:
- Mitigate Risk:
- Improve Collaboration:
This streamlined approach empowers you to efficiently manage your supplier base, ensuring quality and stability for your business on OrientDig.