Big Data Analysis of Weather Condition and Air Quality on Cosmetics Marketing

Zebin Wang, Tong Wu, Xinshuang Zhao, Shuchun Cheng, Genghui Dai, Weihui Dai

Abstract:

Demands of cosmetics are affected not only by the well-known elements such as brand, price, and
customer's consumption capacity, but also by some latent factors, for example, weather and air environment.
Due to complexity and dynamic changes of the above factors, their influences can hardly be estimated
in an accurate way by the traditional approaches such as survey and questionnaires.
Through modeling and statistical analysis of big data, this article studied the impacts of weather condition
and air quality on customer flow and sales of the cosmetics distributors in China, and found several hidden
influencing factors. It provided a big-data based method for the analysis of unconventional factors on
cosmetics marketing in the changing weather condition and air environment.