Data Mining: Consumer Behavior Analysis

The whole world is overloaded via innumerable data like scientific data, financial data, mathematical data, geographic data, employment data, and other various kinds of data. Manually analyzing or summarizing this data is impractical, the reason behind this is incredible increment in data in this generation of information and network distribution. Objective of Data mining is to extract the required information, instruction, and pattern from a huge quantity of information and data by the help of multiple tools and techniques. Therefore, it is very essential to select significant techniques to mine the database, because of the several other varieties of data in data base and every data has their individual mining techniques. In this research paper we are going to analyze the consumer behavior, that can help us not only in the retailer market/industry but we can use it in the medical, online shopping etc. Here we are talking about consumer behavior analysis, so we are taking market industry data. Data mining techniques are most conventional and sufficient technique for behavior analysis. Main target of this paper is to recognize behavior of a consumer, his/her psychological condition, consumer's decision making during purchase and then finding how much suitable methods of data mining are applied to enhance the conventional method. Here association rules are deployed to mine out required rules for customer applied in purchased data in retailers shop or organization. After that the required rule can be used for further required filed line online shopping, medical field etc.