In essence, keyword data-based product selection is to use the operation method to solve the problem of product selection. It cannot develop new products, but it helps operations to find new models with rising trends on the site faster, so as to achieve overtaking. Compared with manual product selection, keyword data-based product selection is less difficult because it can directly show the “feeling” in the form of sales rankings, helping operations to find the direction of product promotion faster.
In this case, on January 15, after 28 ranking captures of the tunic keyword, 41 styles with low rankings but potential were selected from the site. On March 29, a re-investigation found that 10 styles rose to within 10,000, with a hit rate of 24.3%; if the 5 styles that were already within 10,000 during the selection period were excluded, the hit rate was 12.2%. Compared with the 5% to 8% hit rate of experience-based product selection, data-based product selection is indeed more advantageous.
Assume that 100 models are selected for operation at the same time, and the ordinary model sells 1 piece per day, with a minimum order of 20 pieces, while the hot-selling model sells 10 pieces per day, with a minimum order of 500 pieces. According to experience, the cost of goods accounts for about 20% of sales, and the net profit accounts for about 15% of sales. It can be seen that although the increase in the hot-selling rate has increased inventory pressure and commodity costs, it has also brought about a rapid increase in net profit. If the net profit brought by ordinary and hot-selling models is almost the same at a 10% hot-selling rate, then at a 20% hot-selling rate, the net profit brought by the hot-selling model has reached 2.5 times that of ordinary models, and in actual operation scenarios, the net profit brought by the hot-selling model is often higher.
Back to this case, assuming that all 41 products are put on the shelves, the minimum order quantity for the first order is 300 pieces, the average cost is 25 yuan, all are sent to FBA, and the operation is carried out for 3 months, then the cost of the product is 41x300x25=307,500 (yuan).
According to the mentioned ratio, when the cumulative sales reach 307,500-0.2×0.15-6.7 34,421.64 (US dollars), the net profit is equal to the cost of goods, which is equivalent to recovering the initial investment.
Assuming that the unit price of the product is US$20, when 48,190-20=2410 (pieces) are sold, about 8 models are sold out, the cost can be recovered. From the perspective of long-term operation, when the average daily order is stable at 2410-90 27 orders), the initial cost can be recovered within 3 months.
According to experience, if the daily sales of clothing products are 10 pieces, they can enter the top 50,000. In other words, as long as there are 3 links that enter the top 50,000 and achieve dynamic sales, even if the rest of the products become redundant inventory, the balance of income and expenditure can be achieved in 6 months. In order to achieve this goal, it is necessary to use refined operation methods to make the links grow as soon as possible. Although the data has a certain delay, the peak sales season of tunic is from July to September, so even if the preliminary product selection and operation completed in March can lay a solid foundation for the growth of sales in the later period.
However, the direction of keyword selection is mainly in-site selection, which makes the selection method have the problem of low upper limit. The 10 links that successfully selected in this case are mostly ranked between 3000 and 8000, and there is no phenomenal explosion. Professional product selectors can select products that can impact the top 100 of the category. If the ranking data accumulates more than 50,000 and the continuous tracking time exceeds 1 month, the data analysis can be more accurate and the ceiling of the explosion rate will be higher.
Finally, unlike the simple collection of ranking data for product selection, in order to successfully achieve keyword selection, there must be supply chain resource support of related categories. The difficulty of pattern making for clothing products is relatively low, the product production cycle is relatively short, and the risk of infringement is low. The preliminary selection can be completed through two weeks of data tracking. For categories such as 3C and outdoor products, the products need to go through a longer mold opening and production cycle, and more resources need to be invested in the early stage, so it is necessary to arrange the work plan more accurately in order to step on the node for the promotion and operation of hot products.