LitBuy: How to Compare Seller Performance Using Spreadsheet Insights
In e-commerce analytics, comparing seller performance effectively can transform your procurement strategy. By leveraging basic spreadsheet tools like pivot tables and sorting functions, you can systematically identify top-performing sellers based on crucial metrics like Quality Control (QC) accuracy and fulfillment consistency.
Step 1: Organize Your Raw Data
Begin with a clean dataset containing at least the following columns:
- Seller ID/Name
- Order ID
- QC Result
- Fulfillment Status
- Order Date
- Fulfillment Status
Step 2: Create a Seller Performance Pivot Table
Select your data range and insert a pivot table. Configure it as follows:
- Rows:
- Values:
- Count of Order ID (Total Orders)
- Sum of QC Passed (create calculated field if needed)
- Count of On-time Fulfillment
- Values:
Step 3: Calculate Key Performance Metrics
Add calculated columns to your pivot table or source data:
- QC Accuracy Rate:
- Fulfillment Consistency Score:
Step 4: Sort and Rank Sellers
Apply multi-level sorting to your pivot table:
- Primary sort: QC Accuracy Rate (Descending)
- Secondary sort: Fulfillment Consistency Score (Descending)
This instantly reveals sellers who consistently deliver quality products reliably.
Step 5: Visualize Performance Tiers
Use conditional formatting to create a heatmap:
- Green: Above 95% performance
- Yellow: 85-94% performance
- Red: Below 85% performance
Pro Tips for Deeper Insights
- Add time-period filters to track performance trends
- Combine with cost data for value-based ranking
- Create a seller scorecard using weighted averages of both metrics
By systematically applying these spreadsheet techniques, LitBuy can objectively identify top partners, negotiate better terms, and allocate orders to the most reliable sellers - driving both quality and efficiency in your supply chain.