In the daily operation process, sellers need to pay attention to data in various dimensions from time to time, which may cause another problem, that is, one-sided attention to statistics, ignoring the real consumers behind them. User portrait is the most widely used tool in the e-commerce field in the context of big data. Sellers abstract every specific information of buyers into labels, and then use these labels to concretize the user image, so as to provide buyers with targeted products and services.
In our domestic e-commerce industry, user portraits have been widely used in daily operations. In sharp contrast, in Amazon’s cross-border e-commerce industry, the operational ideas of user portraits are still not taken seriously. One reason is that the overall competition of foreign e-commerce is not as fierce as that of domestic competition, and the other is that cross-border sellers lack subjective awareness. According to statistics from the U.S. Department of Commerce, the scale of the U.S. e-commerce market reached 602 billion U.S. dollars in 2019, a year-on-year increase of 14.9%, higher than 13.6% in 2018, and the growth momentum is obvious. In recent years, the growth rate of online retail in our country has continued to slow down. In 2019, the scale of my country’s e-commerce market was 10.63 trillion yuan, a year-on-year increase of 16.5%, lower than 23.9% in 2018. In the context of the continuous growth of the market size, many small and medium-sized sellers are concerned about uploading more products to obtain more traffic, and rarely consider the issue of improving the repurchase rate of the buyer group.
Currently, Amazon’s backend has opened the brand analysis function to brand sellers whose sales exceed a certain level. Sellers can see the age, family income, education, gender, marital status and other information of buyers who have purchased store products in a period of time from the headcount column. However, this information has fewer dimensions, making it difficult to create user portraits, and there are barriers to entry for small or non-brand sellers. Although sellers can also obtain some information through off-site data analysis, Amazon’s main buyers, especially Prime habits, still show great differences. If sellers cannot effectively select products based on the needs of the target buyer group, then later sales will definitely face greater difficulties. At this time, the most effective tool is user portraits.