数据驱动的客户网上购物行为分析和个性化营销策略

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yanmin Li, Chao Meng, Jintao Tian, Zhengyang Fang, Huimin Cao
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引用次数: 0

摘要

在当今竞争激烈的市场环境中,个性化营销已成为企业获取竞争优势的重要手段。为了更好地满足客户需求,企业需要对客户进行准确识别和分类,以实施更精细的市场策略。本研究主要关注客户分类问题。在多个经典深度学习模型的基础上,设计了 BiLSTM-TabNet 模型,并引入鲸鱼优化算法(WOA)进一步提高模型性能,从而提高分类准确性和实用性。实验结果表明,该模型在每个数据集上都取得了优异的性能,准确率和 AUC 值均高于基线方法,在对比实验中也比其他对照模型更具优势。这项研究为个性化营销战略的实施提供了坚实的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Driven Customer Online Shopping Behavior Analysis and Personalized Marketing Strategy
In today's highly competitive market environment, personalized marketing has become an important means for enterprises to gain competitive advantages. In order to better meet customer needs, companies need to accurately identify and classify customers to implement more refined market strategies. This study focuses on the customer classification problem. Based on several classic deep learning models, the BiLSTM-TabNet model is designed, and the Whale Optimization Algorithm (WOA) is introduced to further improve the model performance, thereby improving classification accuracy and practicality. Experimental results show that this model has achieved excellent performance on each data set, has higher accuracy and AUC value than the baseline method, and has advantages over other control models in comparative experiments. This research provides solid support for the implementation of personalized marketing strategies.
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
期刊介绍: ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric. Indexed/​Abstracted: Web of Science SCIE Scopus CAS INSPEC Portico
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