Paper Title
Retail and Customer Profile Analysis and Visualization using Data Mining Techniques

Abstract
A retail store is an establishment owned or run by an individual or manufacturer who sells products directly to the ultimate consumers. Retail store owners purchase or buy good or products in volumes either directly from the manufacturers or from wholesalers at discounted amounts and then sell these products to the consumers with a mark-up for profit. Buyers or customers of retail stores buy products for their personal use without an intention of re-selling them to other customers. The manufacturing companies, wholesalers, sales agents or offices, warehouses, retailers, buyers or customers, and employees are the groups responsible for carrying out the voluminous tasks that jointly determine the realization of corporate plans. Retailers recognize the processes that will likely increase sales and profits, and sales trends determine the methodology using exclusive data from the wholesaler. This study aims to describe the profile of customers in terms of age, gender, and address using customer classification techniques; to determine the sales and profit analysis using classification techniques, and to determine the sales trends within five years using time series model of data mining. The utilization of data mining software is an effective tool to execute classification techniques, while time series analysis is used to identify the sales-profit analysis and sales trend for a certain period of time. After carefully interpreting and validating the outputs of the data mining tool, the researchers were able to successfully identify the sales profit analysis technique and saleable trend from May 1, 2010 to April 30, 2018. Keywords - Sales profit, sales trend, sales transactions, data mining tool, classification analysis, time series techniques