초록

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Abstract ▼ AI-Helper

The visitor tracking data is able to be obtained in indoor environments. Indoor visitor tracking data is recorded with the encrypted visitor's smartphone MAC address as well as when the shopper visited, which area of the store visited, and how long they stayed. As visitor identification information...

The visitor tracking data is able to be obtained in indoor environments. Indoor visitor tracking data is recorded with the encrypted visitor's smartphone MAC address as well as when the shopper visited, which area of the store visited, and how long they stayed. As visitor identification information is stored and data is continuously collected, it enables re-visitor analysis. In this paper, we investigated shoppers' revisitation patterns using data gathered about a year in two clothing stores located in different areas of Seoul. The results of this study are as follows. First, it is shown that the visit intervals of revisitors are influenced by factors such as the day of the week, discount period, etc. In addition, we defined the revisit pattern as the behavior of consecutive visits with visit intervals and suggested the method to mining the revisit patterns. To find revisit patterns to include the mainly visited area of the store, applied genetic algorithm to find appropriate areas for the revisit patterns.

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