The Influence of Customer Movement between Sales Areas on Sales Amount: A Dynamic Bayesian Model of the In-store Customer Movement and Sales Relationship
The Influence of Customer Movement between Sales Areas on Sales Amount: A Dynamic Bayesian Model of the In-store Customer Movement and Sales Relationship
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DOI：
10.1016/j.procs.2017.08.225
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Yuta Kaneko;S. Miyazaki;K. Yada
中科院分区：
文献类型：
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作者：
Yuta Kaneko;S. Miyazaki;K. Yada
近年来，人们积极研究在城市规划、医疗保健和营销中利用地理数据和传感器数据相结合的信息（称为地理空间信息）。在这项研究中，我们专注于记录位置信息的RFID技术（即，空间信息），并估计商店的潜在时空结构作为顾客访问的观察数据。然后，我们提出了一个动态贝叶斯模型的销售分析，它扩展了传统的状态空间模型，包括时空结构。从模型分析的结果可以看出，超市具有明显的以时间段为单位的周期结构和周结构，并且它们与每个销售区域的相邻性动态相关。通过利用销售区域的时空结构的可视化，可以很容易地通知商店经理关于客户访问对销售结果的影响。
Recent years have seen active research that utilizes information combining geographic data and sensor data, called geospatial information, in urban planning, medical care and marketing. In this study, we focus on RFID technology that records position information (i.e., spatial information) of shopping carts in a supermarket, and estimate the latent space-time structure of the store as observation data of customers’ visits. Then, we propose a dynamic Bayesian model for sales analysis, which extends the conventional state-space model to include the spatiotemporal structure. From the results of the model analysis, it is obvious that supermarkets have clear periodic structures in units of time periods and weekly structures, and they are dynamically related to the adjacency of each sales area. By utilizing the visualization of the space-time structure of the sales area, it is possible to easily inform the store manager about the influence of customers’ visits on sales outcomes.