Customer Profile Analysis Using Time Series Model and Clustering

Abstract

The use of data mining in sales and marketing processes of businesses has grown in the past years. It has been an advanced technique to bolster income while at the same time meet customer expectations by analyzing shoppers’ buying behavior and profile [1]. This study focused on the use of customer segmentation and market basket analysis data mining techniques to determine customer profile, purchases, and product stock movements by analyzing sixteen months of sales transactions of a local business and subjecting such dataset in an open-source data mining and visual programing tool called RapidMiner Studio and Shrich MBA to produce different helpful visualizations. After carefully interpreting and validating the outputs of the data mining tool, the researchers were able to successfully identify the saleable products and its subsequent loyal customers and the period/time pattern in which it is saleable.