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A Predictive Modeling of Retail Satisfaction: A Data Mining Approach to Retail Service Industry

A Predictive Modeling of Retail Satisfaction: A Data Mining Approach to Retail Service Industry
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Author(s): M. Hemalatha (M.A.M. College of Engineering, India)
Copyright: 2013
Pages: 15
Source title: Data Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2455-9.ch065

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Abstract

Data mining allows managers to make more knowledgeable decisions by predicting future trends and behaviors. One of the most widely used areas of data mining for the retail industry is in marketing. There are also at least seven methods of analysis or statistical techniques that are commonly used in data mining. It is obvious that the approach to the data mining is the key determinant of the statistical technique to be used. Predictive modeling uses variety of techniques such as linear regression, logistic regression, and their extensions can be used to identify patterns, which can be used to predict the future. This research specifically focuses on the application of multiple regression technique a data mining tool in Indian retail industries to predict the retail satisfaction using store attributes as independent variables.

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