Research on Intelligent cigarette sales forecasting model based on big data technology

Konferenz: CAIBDA 2022 - 2nd International Conference on Artificial Intelligence, Big Data and Algorithms
17.06.2022 - 19.06.2022 in Nanjing, China

Tagungsband: CAIBDA 2022

Seiten: 6Sprache: EnglischTyp: PDF

Autoren:
Wei, Taicheng; Chen, Hao; Liu, Yanbing; Zhu, Haoran (China Tobacco Guangxi Industrial Co., Ltd. Nanning, China)

Inhalt:
Tobacco production enterprises and retailers usually adopt the business strategy of selling according to inventory. Production enterprises need to try their best to ensure the purchase demand of retailers and avoid excessive production. Retailers should not only ensure that the commodity inventory will not be out of stock, but also prevent the economic inefficiency and waste caused by excessive inventory. Therefore, how to make purchase planning in advance through intelligent sales volume prediction is particularly important for retailers to improve their profits. For tobacco production enterprises, it is also necessary to optimize cigarette production and delivery planning through sales volume prediction in order to produce higher cost-benefit. Combined with geographic big data and the historical commodity sales data of cigarette manufacturers and retailers, this paper uses the intelligent sales prediction model to help manufacturers and retailers build a cigarette intelligent prediction model including cloud computing platform, big data analysis center, intelligent sales prediction algorithm and other core modules. Taking six stores in five cities, including Kunshan, Zhangjiaxiang, Taicang, Changshu and Wujiang district, a total of 30 tobacco retailers and one tobacco production enterprise as the experimental objects, the commodity sales in the first quarter and the second quarter is compared. The results show that the inventory turnover rate of tobacco retailers using the prediction model has increased by 30% year-on-year, and the cigarette profit has increased by 7% year-on-year, the cigarette inventory turnover rate of tobacco production enterprises increased by 21%, and the cigarette profit increased by 14% year-on-year. It is proved that the intelligent cigarette sales prediction model can help tobacco production enterprises and retailers reduce the risk of unsalable inventory, and improve the inventory turnover rate and cigarette sales.