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Main Factors Driving the Open Rate of Email Marketing Campaigns

机译:推动电子邮件营销活动开放率的主要因素

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Email Marketing is one of the most important traffic sources in Digital Marketing. It yields a high return on investment for the company and offers a cheap and fast way to reach existent or potential clients. Getting the recipients to open the email is the first step for a successful campaign. Thus, it is important to understand how marketers can improve the open rate of a marketing campaign. In this work, we analyze what are the main factors driving the open rate of financial email marketing campaigns. For that purpose, we develop a classification algorithm that can accurately predict if a campaign will be labeled as Successful or Failure. A campaign is classified as Successful if it has an open rate higher than the average, otherwise it is labeled as Failure. To achieve this, we have employed and evaluated three different classifiers. Our results showed that it is possible to predict the performance of a campaign with approximately 82% accuracy, by using the Random Forest algorithm and the redundant filter selection technique. With this model, marketers will have the chance to sooner correct potential problems in a campaign that could highly impact its revenue. Additionally, a text analysis of the subject line and preheader was performed to discover which keywords and keyword combinations trigger a higher open rate. The results obtained were then validated in a real setting through A/B testing.
机译:电子邮件营销是数字营销中最重要的流量来源之一。它为公司带来了很高的投资回报率,并提供了一种廉价,快速的方式来吸引现有或潜在客户。让收件人打开电子邮件是成功开展竞选活动的第一步。因此,重要的是要了解营销人员如何提高营销活动的开放率。在这项工作中,我们分析了推动金融电子邮件营销活动的开放率的主要因素。为此,我们开发了一种分类算法,可以准确预测广告系列是否会被标记为成功或失败。如果广告活动的打开率高于平均水平,则将其分类为成功,否则将其标记为失败。为了实现这一目标,我们采用并评估了三个不同的分类器。我们的结果表明,通过使用随机森林算法和冗余过滤器选择技术,可以以大约82%的准确性预测广告系列的效果。使用此模型,营销人员将有机会更快地纠正可能严重影响其收入的广告系列中的潜在问题。此外,对主题行和预标题进行了文本分析,以发现哪些关键字和关键字组合触发了较高的打开率。然后,通过A / B测试在真实环境中验证获得的结果。

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