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Sales Prediction and Product Recommendation Model Through User Behavior Analytics 被引量:2
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作者 Xian Zhao Pantea Keikhosrokiani 《Computers, Materials & Continua》 SCIE EI 2022年第2期3855-3874,共20页
The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely af... The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely affected.Therefore,in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience,this study aims to utilize historical sales data for exploring,building sales prediction and recommendation models.A novel data science life-cycle and process model with Recency,Frequency,and Monetary(RFM)analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics.RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level.For the purchase prediction model,XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their.For the product recommendation model,the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes.Moreover,some suggestions are proposed for the marketing department according to the outcomes.Overall,the XGBoost model achieved better performance and better accuracy with F1-score around 0.789.The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness.Furthermore,it recommend specific products to new customers.This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models. 展开更多
关键词 Business transformation behavior analytics customer segmentation sales prediction product recommendation
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First Batch of Anhui Brandname Products Recommended by Anhui Provincial People's Government
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《China's Foreign Trade》 1996年第8期14-15,共2页
Product NameMagang brand high quality carbon steel,common low carbon steel-made cold/hotrolling coil rod(without twisting control)Magang brand integral roll steel-madepassenger train wheel(φ915mm) forrailway useJingj... Product NameMagang brand high quality carbon steel,common low carbon steel-made cold/hotrolling coil rod(without twisting control)Magang brand integral roll steel-madepassenger train wheel(φ915mm) forrailway useJingjing brand electrolytic 展开更多
关键词 Co West First Batch of Anhui Brandname products Recommended by Anhui Provincial People’s Government
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Announcement of Shanghai's Namebrand Products Recommendation Committee
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《China's Foreign Trade》 1997年第4期35-35,共1页
Shanghai’s namebrand products recommending activities were launched in 1995 under the approval of the municipal government, with a view to implementing Shanghai’s namebrand strategy, encouraging enterprises to vie f... Shanghai’s namebrand products recommending activities were launched in 1995 under the approval of the municipal government, with a view to implementing Shanghai’s namebrand strategy, encouraging enterprises to vie for namebrands, and further raising the celebrity and market share for Shanghai’s products. The’Shanghai’s Name- 展开更多
关键词 VIEW Announcement of Shanghai’s Namebrand products Recommendation Committee
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List of Members for the Shanghai's Namebrand Products Recommendation Committee
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《China's Foreign Trade》 1997年第4期35-35,共1页
Shanghai Economic Commission Shanghai Technology Supervision Bureau Shanghai Administration of Industry and Commerce Shanghai Quality Control Association Shanghai Consumers
关键词 List of Members for the Shanghai’s Namebrand products Recommendation Committee
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