research-article

Leveraging email marketing: : Using the subject line to anticipate the open rate

Authors:

Vera L. Miguéis,

Ivo PereiraAuthors Info & Claims

Volume 207, Issue C

https://doi.org/10.1016/j.eswa.2022.117974

Published: 30 November 2022 Publication History

Abstract

Despite being one of the most cost-effective methods, email marketing remains challenging due to the low rate of opened emails and the high percentage of unsubscribed campaigns. Since the sender and the subject line are the only information that the recipient sees at first when receiving an email, the decision to open an email critically depends on these two factors, which should stand out and catch the recipient’s attention. Therefore, the motivation behind this study is to support email campaign editors in choosing a subject line based on its potential quality. We propose and compare several models to measure the quality of a subject line, considering its potential to promote the email opening. The subject lines’ structure and content are explored together with different machine learning techniques (Random Forest, Decision Trees, Neural Networks, Naive Bayes, Support Vector Machines, and Gradient Boosting). To validate the proposed model, a data set of 140,000 emails’ subject lines was used. The results revealed that the models proposed are very promising to support the definition of the email marketing subject lines and show that the combination of data regarding the structure, the content of the subject lines, and senders characteristics leads to more accurate classifications of the potential of the subject line.

Highlights

•

Email marketing is challenging due to the low rate of opened emails.

•

The decision to open an email critically depends on the subject-line.

•

We propose a model support email campaign editors in choosing a subject line.

•

Several subject lines’ structures, contents and ML techniques were explored.

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Cited By

Chitare NCoventry LNicholson J(2023)“It may take ages”: Understanding Human-Centred Lateral Phishing Attack Detection in OrganisationsProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617116(344-355)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3617072.3617116
Sergeeva ARohles BDistler VKoenig V(2023)“We Need a Big Revolution in Email Advertising”: Users’ Perception of Persuasion in Permission-based Advertising EmailsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581163(1-21)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581163
Bernardo ELorenzo KReyes GPonce H(2023)Predict Email Success Based on Text ContentAdvances in Computational Intelligence10.1007/978-3-031-47765-2_6(77-83)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1007/978-3-031-47765-2_6

Index Terms

Leveraging email marketing: Using the subject line to anticipate the open rate

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

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Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 207, Issue C

Nov 2022

1655 pages

ISSN:0957-4174

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Pergamon Press, Inc.

United States

Publication History

Published: 30 November 2022

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Cited By

Chitare NCoventry LNicholson J(2023)“It may take ages”: Understanding Human-Centred Lateral Phishing Attack Detection in OrganisationsProceedings of the 2023 European Symposium on Usable Security10.1145/3617072.3617116(344-355)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3617072.3617116
Sergeeva ARohles BDistler VKoenig V(2023)“We Need a Big Revolution in Email Advertising”: Users’ Perception of Persuasion in Permission-based Advertising EmailsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581163(1-21)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581163
Bernardo ELorenzo KReyes GPonce H(2023)Predict Email Success Based on Text ContentAdvances in Computational Intelligence10.1007/978-3-031-47765-2_6(77-83)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1007/978-3-031-47765-2_6

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