Data Analytics Model for Home Improvement Store

Abstract

The home improvement store is one of the popular retail stores that sells different categories of products for households such as decorations, accessories, and furnishing. The competition among the home improvement stores is very intense where the high business flow has led to a large and overwhelming amount of business data. Thus, poor handling of business data brings some negative impacts on the business. They cannot make a wise business decision if the data are not being utilized to transform it into useful information. The purpose of this study is to design data analytics model for the home improvement store in order to solve these issues. The selected dataset that includes the sales information of the home improvement store will be evaluated and pre-processed before implementing it for analytics. The historical and current business sales will be analyzed to find out the customer preferences toward the products through descriptive analysis especially for customer segmentation using k-mean algorithm. Predictive analytics can also be applied to predict the future business sales or trends by building a regression model using linear regression algorithm. The set of standard and accurate business rules will also be designed for this study based on the dataset. The analysis results will be interpreted and evaluated to identify the model accuracy before conclusions can be made. The analytics results will be visualized in a customizable web-based dashboard so that the clients can apprehend it which the shop owner can make efficient business strategy to increase revenue.