在线购物者购买意愿的数据分析机器学习预测分析

Andrew Frazier, Fatbardha Maloku, Xinzi Li, Yichun Chen, Yeji Jung, Bahman Zohuri
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引用次数: 0

摘要

在一个广泛的基于互联网的商业时代,任何拥有基于网络的店面的公司都在寻找改善客户体验的方法,其最终目标是促进购买。这个过程可以采取多种形式,使用多种策略,但它们都始于一个核心任务。公司必须能够确定谁最不可能和最有可能进行购买。我们建议,通过基本的网页浏览分析,结合人工智能和深度学习组件的机器学习可以提供这种能力,并且是有效细分客户的可行工具。
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Data Analysis of Online Shopper’s Purchasing Intention Machine Learning for Prediction Analytics
In an era of widespread internet-based commerce, any company with a web-based storefront is looking for ways to improve the customer experience, with the ultimate goal of facilitating purchases. This process can take many forms and use many strategies, but all of them start with one core task. The company must be able to identify who is least likely and most likely to make a purchase. We suggest that with basic web browsing analytics, machine learning with integrated artificial intelligence accompany with deep learning component can provide this capability, and is a viable tool for effective customer segmentation.
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