Analysis of Consumer Data on Black Friday Sales Using Apriori Algorithm

M. Maharjan
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引用次数: 4

Abstract

Ability to recognize and track patterns in data help businesses shift through the layers of seemingly unrelated data for meaningful relationships. Through this analysis it becomes easy for the online retailers to determine the dimensions that influence the uptake of online shopping and plan effective marketing strategies. This paper builds a roadmap for analyzing consumer’s online buying behavior with the help of Apriori algorithm. The major factors that affect the consumer’s online buying behavior are convenience, ease of use and perceived benefits. Security is also a major consideration when opting to conduct shopping activities online. This study will helping further analyzing the consumer online buying behavior towards Online shopping which will help the retailers to design appropriate marketing strategies for selling their products online which will further help in development of the country.
基于Apriori算法的黑色星期五消费数据分析
识别和跟踪数据模式的能力可以帮助企业在看似不相关的数据层之间转换为有意义的关系。通过这种分析,网络零售商可以很容易地确定影响网络购物吸收的维度,并制定有效的营销策略。本文利用Apriori算法构建了消费者在线购买行为分析的路线图。影响消费者在线购买行为的主要因素是便利性、易用性和感知利益。在选择进行网上购物活动时,安全性也是一个主要考虑因素。这项研究将有助于进一步分析消费者对网上购物的在线购买行为,这将有助于零售商设计适当的营销策略,在网上销售他们的产品,这将进一步有助于国家的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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