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Multi process prediction model for customer behaviour analysis

机译:用于客户行为分析的多流程预测模型

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摘要

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.
机译:在线购买是零售营销的重大变化之一。随着生活方式的改变,人们不会去购买必需的物品,如礼物,配件和任何电子产品。每个人都开始使用在线购物,并通过在线购物获得良好的报价,从而节省了时间和金钱。在线购物可以帮助客户提前了解商品价格,并能够与其他供应商进行比较。它可以帮助客户从提供低成本和高质量产品的供应商那里购买产品。客户行为分析始终取决于互联网的使用以及多厂商为各种产品提供的服务。非常需要客户行为分析来帮助供应商定义其在线购物,广告,市场细分等策略。这项工作背后的思想是根据客户对各种在线购物活动的互联网使用情况来预测其行为。提出了一种多流程预测模型,利用逻辑回归方法分析客户行为。所提出的模型结果得到了验证,并与许多现有的在线购物客户模型进行了比较。

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