The main image of a women’s jacket and the sales ranking information of two sellers of the jacket.
From the product ranking information, we can see that they were both launched in 2017. Analyzing the sales information and comments of these two products, we can see that they were once hot sellers, but they are no longer hot sellers.
Look at the ranking information of the two products again (their main images are the same, so they can be determined to be the same product).
At the same time, we can also see their positions in the recommendation column.
Through analysis, it is found that the product is hot selling and is still in the growth stage. Although the product being sold is exactly the same as the original product, we can still find a breakthrough point from “listing styles that others have been hot selling”. In terms of probability, the probability of a hot-selling product appearing in various styles is less than 5%. However, the fact that two ordinary stores are listing and selling products that were hot selling one year ago at the same time, and they are able to succeed, shows that the sellers compared the data of multiple platforms when selecting products and conducted careful analysis and judgment.
When listing styles that others have sold well, you can make the following product selection judgments:
●Select products that have been hot-selling in the past year or so (with a large number of reviews and multiple sellers selling the product);
●Now the product is no longer hot-selling:
●The product has a sufficiently large advantage in quality and price.
If the above three conditions are met at the same time, it can be promoted and sold as a sales target for the seller. It should be noted that this method has advantages and disadvantages.
Advantages:
●The method is simple, product selection is convenient, and can be operated in real time;
●The platform data information display is more intuitive, and sales changes are clear at a glance.
●It is impossible to impact the market gap, and the product selection idea is still a follow-up nature:
●The sales volume is very likely not to exceed the first seller who selected the style;
●The data has a strong lag.