Three commonly used indicators in commodity data analysis?

Take the clothing industry as an example to understand three commonly used indicators of commodity data analysis.

1, sold-out rate

The sold-out rate refers to the proportion of the sales volume of a certain commodity to the total purchase volume in a certain period of time. It is an assessment index to recover the sales cost and expenses according to the sales proportion of a batch of goods, which is convenient to determine the degree of commodity sales and can be liquidated at a discount. (from Baidu Encyclopedia)

Combined with clothing, the sales life cycle of general clothing is three months. If the sales rate of clothing is less than 60% within three months, not because of season, weather and other reasons, it can be roughly judged that the sales of this product are problematic, of course, it is not necessary to wait until three months to determine. Within three months, the first month's size and color matching was completed, and the sold-out rate was 40-50%, the second month was about 20-25%, and the third month was only 5- 10% due to code breakage and other reasons. When the sales rate in the first month is far below 40% and there is no other reason, we should pay special attention to strengthen the display or promotion.

Take the following figure as an example. Because it is the data of 8 and 9, it is easy to find that the sales rate of shirts and dresses is relatively low because of the weather. When making decisions, you can consider stopping or reducing purchases after September; The sales rate of windbreakers and sweaters, which should be best-selling, is also very low, so we need to think about where the problem lies, style or price or location? In order to make the next sales plan.

2. Inventory to sales ratio

Stock-to-sales ratio is an index to check whether the inventory is reasonable, such as monthly stock-to-sales ratio and annual average stock-to-sales ratio. The calculation method is: monthly storage-sales ratio and monthly average inventory/monthly sales. A high proportion means too much inventory and poor sales. If it is too low, it may be that the output cannot keep up. (from Baidu Encyclopedia)

Whether the setting of warehouse-to-sales ratio is scientific and reasonable determines whether order supply can really extend to order production; Second, whether enterprises can truly adapt to the market, respect the market and respond to orders; Third, whether the inventory enterprises can truly meet the market, do not overstock, and do not stop filing when managing.

The more popular the goods, the smaller the ratio of inventory to sales we need to set, which can better accelerate the turnover efficiency of goods; The more unsalable the goods, the greater the warehouse-to-sales ratio. We can maintain the warehouse-to-sales ratio at a certain level through sales and distribution, and it is not allowed to be too high or too low. Once the ratio of deposit to sales is too high or too low, it means that the daily sales and distribution work is not done well. In other words, don't wait until the stock-to-sales ratio reflects the abnormal inventory.

Similarly, looking at the picture, the ratio of storage to sales of sweaters and shirts is two typical examples.

3. Horizontal effect

Floor efficiency is mainly used to calculate the operating efficiency of shopping malls and measure how much turnover each floor area can generate.

Different locations of the store attract different numbers of customers. The entrance to the first floor is usually the most attractive place. In such a prime location, you must place a counter that can get the most profit. Although the core index of the store is profit, the index that can represent the competitiveness of the store is not profit, but an intensity index, that is, floor efficiency and human efficiency, that is, contribution per square meter and per capita contribution. This is an indicator that can be compared among stores, and it is also a key indicator that can fully reflect the basic competitiveness of stores.

The floor efficiency of many specialty stores is ahead of peers, which is the result of in-depth analysis of passenger flow and consumer shopping in the early stage and optimization of store layout, dynamic line and category design. Therefore, floor efficiency is also very important for a clothing store.

The following figure is a complete report for your reference (it is recommended to see the big picture).

The above data charts and data reports are from BDP Personal Edition!