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首页> 外文期刊>International journal of knowledge engineering and soft data paradigms >Estimation of customer behaviour in sales areas in a supermarket using a hidden Markov model
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Estimation of customer behaviour in sales areas in a supermarket using a hidden Markov model

机译：使用隐马尔可夫模型估算超市销售区域的顾客行为

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摘要

Many studies have been devoted to grasping the customer's purchase decision process by using point-of-sales data. A few recent studies gathered customer shopping path data by using radio frequency identification technology in addition to point-of-sales data in an attempt to grasp customers' in-store behaviour in more detail. However, customer shopping path data only provides coordinate information in a store, whereas an estimation of the state of customer behaviour is needed. This paper proposes a customer behaviour model based on a hidden Markov model, which is used to estimate two states of customer behaviour in a sales area, namely, 'pass by' and 'stop.' In addition, we propose three evaluation measures of sales areas: non-purchase rate after stop, purchase rate after pass by, and stop rate based on the estimated state of customer behaviour. These measures are useful for the assessment of sales areas. In addition, shopping momentum is known as a state of mind that induces a subsequent purchase while shopping. We identify the customers who are experiencing shopping momentum by using point-of-sales and customer shopping path data and compare their purchase results with those of other customers.
机译：许多研究致力于通过使用销售点数据来掌握客户的购买决策过程。近期的一些研究除销售点数据外，还通过使用射频识别技术收集了顾客的购物路径数据，以更详细地掌握顾客的店内行为。然而，顾客购物路径数据仅提供商店中的坐标信息，而需要估计顾客行为的状态。本文提出了一种基于隐马尔可夫模型的客户行为模型，该模型用于估计销售区域中客户行为的两种状态，即“通过”和“停止”。另外，根据顾客行为的估计状态，提出了三种销售区域的评价指标：停止后的非购买率，经过后的购买率，停止率。这些措施对于评估销售区域很有用。此外，购物动能被称为一种心智状态，在购物时会引发随后的购买。我们通过使用销售点和客户购物路径数据来识别正在经历购物势头的客户，并将其购买结果与其他客户的购买结果进行比较。

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