Analysing the Purchase Behavior of a Customer for Improving the Sales of a Product
M. N. Saroja1, S. Kannan2, K. R. Baskaran3

1M. N. Saroja, Department of Information Technology, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2S. Kannan, Department of Electronics and Communication, Sree Sakthi Engineering College, Coimbatore (Tamil Nadu), India.
3K. R. Baskaran, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript Published on 09 January 2019 | PP: 173-175 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2028017519/19©BEIESP
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Abstract: Modern techniques such as predictive analytics have gained a lot of research attraction these days. In the competitive world, it is important for a business people to predict the pulse of customer to shine. With predictive analytics, it is possible to see what a customer will buy next. The goal is to increase the profit earned by a company. In this paper, various hypothesis tests have been conducted for analysing the purchases of a customer. Initially, the purchases have been analysed by grouping the purchases gender wise and by analysing what group of people buy more products. It also finds out which group prefers for promotion codes and discounts and for what type of products they preferred more. In which store, the sales of products are more and in which state, the sales are maximum. Based on this, techniques for improving the sales of a product is suggested.
Keywords: Data Analytics, Purchasing Behaviour, Product Recommendation, Predictive Analytics, Data Mining.
Scope of the Article: Data Mining