Multi process prediction model for customer behaviour analysis Online publication date: Tue, 03-Apr-2018
by D. Kalaivani; T. Arunkumar
International Journal of Web Based Communities (IJWBC), Vol. 14, No. 1, 2018
Abstract: Online purchase is one of the big changes to the retail marketing. As the lifestyle changed, the people are not going to shop for purchasing required items like gifts, accessories and any electronic items. Everyone started to use online and saving their time and money by getting a good offer through online shopping. Online shopping helps the customer to know the price of the item in advance and able to compare the price with different vendors. It helps the customer to buy the item from the vendor who offers the item with low-cost and good quality. The customer behaviour analysis always depends upon the usage of the internet and service provided by the multi vendor for the various products. Customer behaviour analysis is very much needed to help the vendors to define their strategy for online shopping, advertising, market segmentation and so on. The idea behind this work is to predict the customer behaviour based on their internet usage for various online shopping activities. Multi process prediction model is proposed to analyse customer behaviour using logistic regression method. The proposed model result is validated and compared with many existing online shopping customer models.
Online publication date: Tue, 03-Apr-2018
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