Abstract
This research study contributes towards understanding the customer’s behaviour dynamics. In business analysis, it is very important not to ignore the fact that the interaction between human beings implicitly includes an emotional dimension. The research methodology includes the following: (1) customer purchase pattern prediction methods based on correlation; (2) augmentation of data set by using genetic algorithms; and (3) multiple regression models. The analysis indicates how the hobby of a customer is directly related to the purchase patterns and satisfaction level. We applied business intelligence (BI) techniques and concluded that, by using multiple regression method is possible to evaluate the level of customer satisfaction up to the upper limit of security of about 90%. BI tools could be used to employ significant achievements in specific fields based on open innovations. This paper aims at providing further practical guidance in this innovative research field by using a mix of interdisciplinary methods and techniques.
Highlights
The core idea of business intelligence (BI) is to recognise the behavior of the customer and to predict their purchase pattern for improvement of the business as well as for a better environmental sustainability
Real True Positive RatioTPR values for satisfaction level for ten hobbies after data enhancement are depicted in Figure 6 presented below
The data records are clustered on the basis of weights using correlation technique, which is explained in the section 3.1
Summary
The core idea of business intelligence (BI) is to recognise the behavior of the customer and to predict their purchase pattern for improvement of the business as well as for a better environmental sustainability.
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