Analysis and Visualization of ID-POS data how purchasing behavior changes along with annual seasons.

Abstract

These days IDThese days ID-POS data are widely used with AI to understand consumers and improve retailing services. We suggest a way to make longitudinal research of ID-POS data to understand how and why any change in people's purchasing along with seasons with pLSA and visualized our result. Many people change what they buy in each season, but others don't in some seasons. So we investigated the reason why some people don't change their purchasing in some seasons with Bayesian network. The result told us that the seasonal purchasing changes are effected from consumers' family members and their preference. The result implicates that some changes in consumers' family members can cause some change of their purchasing behavior. Visualizing the result of AI's data analysis will help us understand what AI tell us and decide what we do to improve our business or lives.