Dynamic E-commerce Recommendations Through Seasonality and User Demographics

In recent years, e-commerce platforms have emerged in an endless stream, including Amazon and eBay in the high-end international market, Tmall and JD.com in the high-end Chinese market, Pinduoduo and Taobao in the low-end market. It is not so difficult for many companies to share a piece of the online shopping business. However, due to the serious homogeneity of online shopping platforms, it is difficult for users with special purchasing needs to find suitable e-commerce platforms. At the same time, different e-commerce platforms have different user stickiness for different products. Therefore, understanding users’ preferences and reasons for purchasing on the platform can help enterprises improve the efficiency and accuracy of marketing. For example, after big data analysis, companies can push different products to different groups of people with more accurately and more appropriate prices. This paper chooses four popular e-commerce platforms at present: JD, Taobao, Pinduoduo and Tall as the analysis objects. Analysing consumers’ purchasing tendency and reasons for different platforms by investigating. For different online review systems, reviews and comments have different effects on sales. Under the classified evaluation system, the total number of reviews and the number of positive comments have a significant positive impact on sales. Negative reviews or comments have a significant negative impact on sales . Hence, in this experiment, the author hopes to collect feedback from consumers to analyse whether the four platforms are successful in marketing within different consumer groups, and to analyse the reasons why different consumer groups are attracted to these four platforms. According to the survey, users tend to have obvious preferences when buying different products. For example, they tend to choose JD.com when buying electronic products, while they tend to choose Taobao and Pinduoduo when buying low-priced daily necessities. At the same time, the author will also classify theconsumers participating in the survey according to age and gender in order to analyse the impact of these factors on the choice of purchasing platform.