Research on influencing factors of pharmaceutical e-commerce sales based on web crawler and support vector machine

Abstract

Based on the current background of the rapid development of the pharmaceutical e-commerce industry, this paper provides an in-depth discussion of the factors affecting pharmaceutical e-commerce sales. With the help of Python crawler technology, the pharmaceutical e-commerce data of Alibaba Health platform is collected with GanMaoLingKeLi(999) as an example. Using support vector machine (SVM), according to the selected characteristic indicators, different schemes are set to predict the sales of pharmaceutical products and determine the influencing factors of pharmaceutical e-commerce sales. The results show that comment characteristics, transaction characteristics, shop characteristics, service characteristics and product characteristics all have different degrees of influence on product sales. Among them, the influence of comment characteristics is the most significant. Based on these results, merchants should attach great importance to the construction of review content and improve the quality of pharmaceutical services to attract and retain consumers. The government should promote the pharmaceutical e-commerce industry to improve service quality and encourage technological innovation. Third-party platforms should optimise website design and strengthen brand image through live broadcasting and other means.