Amazon management and basic operations have a common goal, which is to use scientific methods to improve resource utilization and strive to increase sales as much as possible with limited resources. Under this goal, front-line operators need more effective data tools to track the specific daily sales of stores.
First, due to the B2C nature of the Amazon platform, its platform sales have obvious cyclical changes, which are specifically manifested in the decrease in sales on weekends and the recovery from Monday to Friday with slight fluctuations.
Based on experience, the sales of this store are at a medium level, so its performance change trend represents the overall sales trend of a certain field of Amazon under certain circumstances. By comparing the calendar, the following conclusions are drawn.
1 Wednesday in the United States is at the lowest sales trough of the week, but not the lowest value.
2 Saturday in the United States is at the lowest sales trough of the week, and it is likely to be the lowest value.
3 The sales value is in the growth period from Sunday to Tuesday and Thursday to Friday in the United States.
Through the above-mentioned empirical verification, it can be found that the store sales cycle in weeks, so the weekly weight index can be used as an indicator.
The calculation method of the weekly weight index of the operation team/enterprise is as follows:
Step.1 Collect the sales data of each store in the last full year;
Step.2 Eliminate outlier data such as Prime Day, Black Friday, and deals;
Step.3 Sort the remaining data by week, with the row label being the week number and the column label being the day of the week, and calculate the average daily sales;
Step.4 Take the sales data with the lowest average daily sales and set its daily sales weight index to 1. Divide the average of the other 6 days by the average of the day to obtain the daily sales weight index of the other 6 days;
Step.5 Add up the daily weight index to get the final weekly weight index. The minimum weekly weight index should be 7. The larger the weekly weight index, the more unstable the sales.
The operator can calculate the average daily performance from Monday to Sunday for the whole year through the daily performance of each week in a year, and then set the lowest value of the average daily performance “6091.86”, that is, the daily sales weight index of Sunday, to 1, so the daily sales weight index from Monday to Saturday can also be obtained through calculation, and finally the weekly weight index is obtained. “The weekly weight index is also called the “enterprise weekly weight index” and belongs to macro management data.
With the weekly weight index of the overall operation team and the enterprise, the daily weight index of each store in the team or enterprise can be reversed, and different performance standards can be specified according to the specific situation of each store.
The calculation method of the daily weight index of a single store is as follows.
Step.1 Count the store sales data of the last two months and one month of the same period last year, and eliminate outliers;
Step.2 Calculate the filtered data in units of weeks to obtain the average daily sales and average weekly sales from Monday to Sunday;
Step.3 After the final calculation, the daily weight index of a single store is;
Daily weight index of week N = (average daily sales of week N / average weekly sales) Weekly weight index.
Since the daily weight index of a single store has a short range of values, it uses three months of data to estimate one month’s sales, so it needs to be updated once a month to ensure the reference of the data.
Finally, the operator needs to predict the appropriate daily weight index for holidays and promotions. For the US site, most holidays are defined by weekdays. Since there will be a shopping peak and a trough before the holiday, most promotions will also be chosen to start before the holiday. Therefore, you can simply compare the sales data of the past 2 to 3 years and use: daily weight index = daily sales/unit weight (sales) value to determine the daily weight index of the promotion day and the week before the holiday.