Navigating Chinese marketplaces like Weidian and Taobao can be daunting. LoongBuy's powerful spreadsheet dataset simplifies this process by helping you identify reliable sellers efficiently. This tutorial will show you how to use its filter functions to make informed purchasing decisions.
Understanding the LoongBuy Spreadsheet Columns
The core of LoongBuy's utility lies in its structured data. Key columns for verification include:
- Product Category:
- Feedback Score:
- Average QC Success Rate:
- Additional data points like store name, link, and transaction volume are also provided.
Step-by-Step Filtering for Reliable Sellers
Follow these steps to narrow down the spreadsheet to the most trustworthy stores.
Step 1: Filter by Product Category
First, locate the "Product Category" column. Use the filter dropdown menu to select your specific product of interest (e.g., "Men's Sneakers," "Women's Dresses," "Electronics"). This immediately removes irrelevant sellers from view, allowing you to focus on specialists in your desired field.
Step 2: Sort and Filter by Feedback Score
Next, sort the "Feedback Score" column in descending order. Generally, a higher score indicates greater buyer satisfaction. For a more stringent search, apply a filter to only show sellers with a score above a certain threshold (e.g., 4.7 or 4.8 out of 5). This prioritizes sellers with a proven track record of good service.
Step 3: Prioritize with Average QC Success Rate
This is a critical filter for quality. The "Average QC Success Rate" shows how consistently a seller's items pass agent inspections. Apply a filter to display only sellers with a high rate—95% and above is an excellent benchmark. This significantly reduces the risk of receiving substandard or misrepresented items.
Step 4: Cross-Reference and Final Selection
With your refined list, examine the remaining sellers. Look for stores that perform well in all three categories. A seller with a high feedback score and
Pro Tips for Effective Use
- Combine Filters:
- Check Volume:
- Data is Dynamic: