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A Study on Prediction of Sales Amount of Each Product Category Using Weather Information
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유통업에서 날씨정보를 활용한 상품별 매출 예측 방안에 관한 연구

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Type
Academic journal
Author
Journal
The Korean Data Analysis Society Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제17권 제1호 KCI Accredited Journals
Published
2015.1
Pages
173 - 182 (10page)

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A Study on Prediction of Sales Amount of Each Product Category Using Weather Information
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Abstract· Keywords

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The big retailers in South Korea show seasonal trend with the change of sales amount. This trend is observed annually. Temperature and rainfall amount are influential factors in the change of sales amount. Sales amount increases at the start of spring and reach its height during summer period. Winter shows the least amount of sales. The sales amount of each retail store is predictable through this trend. Big retailers are already applying sales prediction models to assign budget and marketing cost to each store. The ordering system is enhanced through these models as well. These days, retailer's sales growth rate showed negative growth even when these models were attempted. The solution is to enhance the efficiency of marketing and not quantitative growth through building more stores. Sales prediction is used to calculate the best time to increase customer marketing response rate. This paper shows the process of building daily sales prediction model through weather data and retailer’s sales data with stores.

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