This analysis section mainly analyzes the following data:
FBA/FBMO proportion changes; FBA/FBM daily absolute data changes: FBA/FBM relative data changes per cycle; sales volume fluctuations and trends Variety.
1. Changes in the proportion of FBA/FBM.
While recording the total sales volume and total sales volume every day, it is necessary to separately record the sales volume and sales value of FBA and FBM. The fluctuation in the proportion of the two indicates the progress and speed of the store’s new product development;
When the proportion of FBA/FBM is relatively high, it means that the store is in a stable stage, new product development is progressing slowly, and the risk resistance to future style updates and seasonal iterations is low;
When FBA When the /FBM ratio is average, it shows that there is still a lot of room for optimization in FBA sales. At the same time, the high proportion of self-delivery shows that the store is making good progress in new product development and has higher styles;
Update If you resist risks and nothing unexpected happens in the next 1 to 3 months, you can maintain or even rush to higher sales;
When the FBA/FBM ratio is low, it indicates that the store is in a period of rapid growth ( (Except for small stores), sending FBA is a top priority at this time. At the same time, because the self-delivery logistics speed is slow and the review update frequency is low, the biggest risk for the store at this time is that the hot-selling listing will quickly generate a large number of negative reviews after sending FBA. In this case, it is necessary to Strictly control product quality. If the quality is not good enough, we would rather not issue FBA to ensure that the listing survives longer and maximizes profits.
2. Daily absolute data changes of FBA/FBM.
Monochronous changes: This value is recorded so that when the store reaches a certain size (for example, daily average of 5,000+ US dollars), we can understand the fluctuation pattern of the store’s business category’s traffic within one cycle (generally one cycle Set to a week), for example, the traffic is minimum every Sunday, there is a low traffic peak every Thursday, there is a small traffic peak between X:00~X:00 every day, etc.
By looking for these patterns and then looking for the underlying reasons behind them, we can understand the behavioral logic behind the store’s customer groups.
3. Relative data changes of FBA/FBM per cycle.
Year-on-year changes: This value is recorded to analyze whether the store’s FBA/FBM sales volume is in an increase/decline stage compared with the same time in the previous cycle; at the same time, this value can also reflect when a certain batch of FBA products enters the market. After being put into stock, has there been any significant growth in its sales volume?
4. Sales volume fluctuations and trend changes.
It can be divided into two types of analysis, namely qualitative analysis and quantitative analysis:
(1) Qualitative analysis. That is to determine whether sales have increased. Just use the chart function that comes with the Excel software to visually reflect the increase in sales. The judgment method is relatively simple and will not be described in detail here.
(2) Quantitative analysis. That is, predicting future sales based on past sales. A commonly used method in econometrics is used here: the least squares method (note that this method is a rough prediction rather than a precise prediction. When the store sales data is large, other methods need to be replaced), and its setting method in Excel.
This method can generate a forecast sales data based on daily data.
The meaning of the reference data calculated by this method is: assuming the sequence calculated by the least squares method is {a}, then when the store is experiencing an increase in sales, the corresponding number in the sequence is likely to be the lower limit of the sales volume; when When store sales decline, the corresponding number in the sequence is probably the upper limit of sales: when store sales are in a stable period with certain fluctuations, this value will gradually decrease as a reference as the fluctuations increase.