Generation of Personalized E-mail Subject Lines

Abstract

The online presence of e-commerce platforms, publishers, and other businesses has been increasing with the rise of internet use. These companies regularly expose their (potential) customers to massive amounts of media and products. It is vital for these companies to elicit interactions from these individuals in order to sell products or subscriptions. Engagement with online items, such as articles or products, are often measured using clicks. A well-known and proven method for improving online interactions is the use of clickbait. However, this practice is known to degrade the reputation of businesses. Widespread use of obvious clickbait is, therefore, not a sustainable solution for reputable companies. Research into alternative solutions to foster engagement is mostly taken from the perspective of the consumer. These solutions mainly involve various recommender algorithms that match consumers with items and articles that interest them. However, research from the perspective of the producer is extremely limited. The producer of the content has different incentives than the consumer of the content. Their main goal is to elicit an interaction from the consumer, while the consumers' main goal is to find something that interests them.

In this thesis, inspired by the work on personalization for consumers, we make the producer the main stakeholder. We explore whether the personalization of subject lines for groups of users with similar behaviour patterns and interests improves the engagement of consumers on newsletters. With the digital marketing company Basedriver as the use case, we personalized the headlines of marketing e-mails in newsletters and performed experiments to analyse the effectiveness of our technique. We hypothesise that e-mail marketeers can improve engagement by personalizing subject lines to address the personal interests of consumers. By looking at the content of articles previously clicked by consumers, they can be grouped into user groups with similar interests. Information on the interests of users from these groups can then be leveraged to generate a subject line addressing the interests of the group. The historic customer behaviour data and platform used for the validation of our new personalization strategy was provided by Basedriver and Hearst, who assisted in the research. Basedriver also provides the platform for collecting the data from the experiment.