Refund performance data is a statistical data of refund rate from another time dimension. This data has a direct impact on store traffic and single product traffic, that is, the more sales and the fewer refunds in a single week, the better traffic performance will be.
In the refund performance section, the classification of refund reasons is more refined. The main reason for refund is long delivery time. The other refund reasons are all reasons that we can check immediately and optimize the corresponding processes. Click the “Product Details” link on the right to determine which products need to be reviewed immediately based on the data in the “Item Damaged” column. Because the number of refunds is not large, it is necessary to trace back to previous data to check whether this situation has occurred repeatedly, and arrange logistics-related personnel to make improvements.
The data in the “Detailed List for Each Country” is very helpful for us to optimize the performance data of the store and increase the operating gross profit. Regularly selecting countries with extremely high refund rates and making improvements or blocking them can help us save unnecessary operating losses.
Here we also need to follow the single product traffic detection method mentioned above and conduct continuous detection on individual countries with high refund rates. At least 4 weeks of data are needed. We cannot lose customers from a country because of one or two problems.
User feedback and counterfeit rate performance
User feedback data is a more detailed display of homepage data.
The counterfeit rate performance data refers to the proportion of counterfeits found by Wish during regular weekly product inspections. If this data exceeds 5%, the store will lose the qualification of an honest store.
Sales chart and user service chart
The sales chart uses a curve chart to display the collection volume, traffic and sales trend of the store or single product. Merchants can view the data of a single product through the filter menu in the upper right corner, or view the data according to different time dimensions such as month, week, day, etc., which helps merchants save time in exporting data from sales performance for analysis.
The user service chart compares several core data of the store with the standards set by Wish for these data in the form of a curve chart to remind merchants to adjust the relevant processes for data exceeding the standard.