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Predicting Purchase Behavior of Website Audiences
International Journal of Electronic Commerce ( IF 5 ) Pub Date : 2018-09-17 , DOI: 10.1080/10864415.2018.1485084
Saar Kagan , Ron Bekkerman

ABSTRACT This paper proposes a methodological framework that extends the advantages of behavioral targeting while preserving the privacy of the individual. Instead of profiling individual users according to their general interests, we profile website audiences according to their online purchase behavior. This presents a trade-off between looser, aggregate audience profiling and deeper understanding of actual purchase behavior, the holy grail of online advertising. Our framework is based on the analysis of raw clickstream data of Web users who explicitly agreed to participate in an online audience panel. We experiment with data collected by an online analytics company, SimilarWeb, which consists of 3,463,796 records of online purchases and 1.1 billion records of Website visits. We train a multilabeled classification model on the clickstream of panel members with distinctive online purchase profiles to predict the purchase potential of the entire panel. We aggregate the individual purchase behavior profiles (both ground-truth and predicted) into purchase behavior profiles of Web domain audiences and test the resulting methodology on 3,408 Web domains, with very promising results. If privacy-related regulation tightens up in the near future, the proposed panel-based, purchase-focused ad targeting mechanism might be the panacea for online advertisers.

中文翻译:

预测网站受众的购买行为

摘要 本文提出了一种方法框架,该框架扩展了行为定向的优势,同时保护了个人隐私。我们不是根据个人用户的一般兴趣来分析他们,而是根据他们的在线购买行为来分析网站受众。这在更松散、聚合的受众分析和对实际购买行为的更深入理解之间进行了权衡,这是在线广告的圣杯。我们的框架基于对明确同意参与在线受众小组的 Web 用户的原始点击流数据的分析。我们用在线分析公司 SimilarWeb 收集的数据进行实验,其中包括 3,463,796 条在线购买记录和 11 亿条网站访问记录。我们在具有独特在线购买配置文件的小组成员的点击流上训练多标签分类模型,以预测整个小组的购买潜力。我们将个人购买行为概况(真实和预测)聚合到网络域受众的购买行为概况中,并在 3,408 个网络域上测试由此产生的方法,结果非常有希望。如果在不久的将来与隐私相关的监管收紧,那么提议的基于面板、以购买为中心的广告定位机制可能是在线广告商的灵丹妙药。我们将个人购买行为概况(真实和预测)聚合到网络域受众的购买行为概况中,并在 3,408 个网络域上测试所得方法,取得了非常有希望的结果。如果在不久的将来与隐私相关的监管收紧,那么提议的基于面板、以购买为中心的广告定位机制可能是在线广告商的灵丹妙药。我们将个人购买行为概况(真实和预测)聚合到网络域受众的购买行为概况中,并在 3,408 个网络域上测试由此产生的方法,结果非常有希望。如果在不久的将来与隐私相关的监管收紧,那么提议的基于面板、以购买为中心的广告定位机制可能是在线广告商的灵丹妙药。
更新日期:2018-09-17
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