Newly subscribed! Effects of e-mail newsletters on news-reading habit and subscriber retention during onboarding: evidence from clickstream and subscription data

ABSTRACT

Despite the increasing popularity of e-mail newsletters, there have been few studies that examine the effects of signing up for e-mail newsletters among news subscribers, especially its role in enhancing news reading behaviors and subscriber retention for new subscribers. This study investigates how e-mail newsletter sign-ups influence news-reading habits and subscriber retention during onboarding. Using single-source data that combine clickstream data from news sites, e-mail newsletter sign-up records, and payment histories of 16,284 new digital news subscribers across four major markets in the U.S. this study finds that signing up for e-mail newsletters improves news reading habits and digital news subscription duration, with an additive effect of the number of e-mail newsletters signed up for. Regarding the retention mechanism, signing up for e-mail newsletters contributes to retention by helping new subscribers read more frequently and intensely (measures of reading habit), which in turn positively affects subscriber retention.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ Note that the focal causal variables (newsletter sign-up status and the number of newsletters signed up for) precede the two mediating variables of news reading habit behaviors (regularity and intensity), which precede the outcome variable (retention). We choose these times between the variables to eliminate reverse causality and simultaneity.

² When the reading habits are not controlled for (Equation (5)(5) $\mathit{h}\left(\mathit{t}\right)=h_0\left(\mathit{t}\right)\mathit{exp}\left({\beta }_1\mathit{Newsletter}+{\beta }_2\mathit{App}+{\beta }_3\mathit{Mobile}+{\beta }_4\mathit{Tablet}\text{break}+{\beta }_5\mathit{Market}+{\beta }_6\mathit{Month}+{\beta }_7\mathit{Market}\times \mathit{Month}\right)$(5) , for example), it is predicted that a subscriber’s hazard rate decreases by 15.9% = = (1-e^−0.174) × 100% if she signs up for an e-mail newsletter in the first month versus not. However, when the reading habits are controlled for (Equations (7)(7) $\begin{array}{r}\mathit{h}\left(\mathit{t}\right)=h_0\left(\mathit{t}\right)\mathit{exp}\left({\beta }_1\mathit{Newsletter}+{\beta }_2\mathit{App}+{\beta }_3\mathit{Mobile}+{\beta }_4\mathit{Tablet}+{\beta }_5\mathit{ln}\left(\mathit{Regularity}\right)\text{break}+{\beta }_6\mathit{ln}\left(\mathit{Intensity}\right)+{\beta }_7\mathit{Market}+{\beta }_8\mathit{Month}+{\beta }_9\mathit{Market}\times \mathit{Month}\right)\end{array}$(7) , for example), the hazard rate of a subscriber decreases by 11.4% = (1-e^−0.121) × 100% if she signs up for an e-mail newsletter in the first month versus not. Comparing these two figures suggests that the direct effect accounts for about 71.6% = (11.4/15.9) × 100% of the total effect.

³ In Equations (9)(9) $\mathit{ln}\left(\mathit{Regularit}{y}_{\mathit{it}}\right)={\alpha }_{\mathit{i}}+{\xi }_{\mathit{t}}+{\beta }_1\mathit{ln}\left(\mathit{NewsletterNu}{m}_{\mathit{it}}\right)+{\beta }_2\mathit{ln}\left(\mathit{NewsletterCancelNu}{m}_{\mathit{it}}\right)+\mathit{Control}\mathit{Variable}{s}_{\mathit{it}}+{\epsilon }_{\mathit{it}}$(9) and (10(10) $\mathit{ln}\left(\mathit{Intensit}{y}_{\mathit{it}}\right)={\alpha }_{\mathit{i}}+{\xi }_{\mathit{t}}+{\beta }_1\mathit{ln}\left(\mathit{NewsletterNu}{m}_{\mathit{it}}\right)+{\beta }_2\mathit{ln}\left(\mathit{NewsletterCancelNu}{m}_{\mathit{it}}\right)+\mathit{Control}\mathit{Variable}{s}_{\mathit{it}}+{\epsilon }_{\mathit{it}}$(10) ), we do not need to add the market and month dummy variables because subscriber- and month- fixed effects are controlled for (α_i and ξ_t). On the other hand, in Equations (11)(11) $\mathit{ln}\left(\mathit{Duratio}{n}_i\right)={\beta }_0+{\beta }_1\mathit{ln}\left(\mathit{NewsletterNu}{m}_{\mathit{it}}\right)+{\beta }_2\mathit{ln}\left(\mathit{NewsletterCancelNu}{m}_{\mathit{it}}\right)+\mathit{Control}\mathit{Variable}{s}_{\mathit{it}}+{\epsilon }_{\mathit{it}}$(11) and (12(12) $\mathit{ln}\left(\mathit{Duratio}{n}_i\right)={\beta }_0+{\beta }_1\mathit{ln}\left(\mathit{NewsletterNu}{m}_{\mathit{it}}\right)+{\beta }_2\mathit{ln}\left(\mathit{NewsletterCancelNu}{m}_{\mathit{it}}\right)+{\beta }_3\mathit{ln}\left(\mathit{Regularit}{y}_{\mathit{it}}\right)+{\beta }_4\mathit{ln}\left(\mathit{Intensit}{y}_{\mathit{it}}\right)+\mathit{Control}\mathit{Variable}{s}_{\mathit{it}}+{\epsilon }_{\mathit{it}},$(12) ), we include the market and month dummy variables because subscriber- and month-fixed effects are not included.

Additional information

Notes on contributors

Su Jung Kim

Su Jung Kim is an Associate Professor at USC Annenberg. She is interested in how audience behavior takes shape in the digital media environment, especially the formation, patterns, and impacts of audience engagement in the digital media environment. Her research has examined cross-platform media repertoires and information sharing behaviors (e.g., eWOM, online reviews, and news sharing), as well as the persuasive effects of audience engagement, for example, technology adoption, purchase decisions, and civic/political participation. Methodologically, she employs the tools of computational social science to trace, collect and analyze individuals’ digital footprints along with other quantitative research methods. Her work has been published in New Media & Society, Journal of Advertising, Journal of Interactive Marketing, Journalism & Mass Communication Quarterly, Digital Journalism, Journal of Broadcasting & Electronic Media, Decision Support Systems, and International Journal of Communication among others.

Ho Kim

Ho Kim is an Associate Professor of Digital and Social Media Marketing at University of Missouri-St. Louis. He is interested in how newspapers can leverage digital technologies (e.g., paywalls and online newsletters) and develop digital strategies to improve their financial outcomes. His other research interests include how eWOM and online search influence consumers’ purchase decisions, how consumer journey unfolds on online platforms, and how crowd patronage on online platforms affects the creative performance of digital creators such as open-source software developers. He uses econometric/statistical models and content analysis techniques as his primary research methodology. He has published at leading journals in marketing and business, such as Journal of the Academy of Marketing Science, Journal of Business Ethics, International Journal of Research in Marketing, Journal of Interactive Marketing, and European Journal of Marketing. His research has been featured at various outlets, including Forbes, Huffington Post, and The Globe and Mail. He earned his PhD in 2013 in Marketing from UCLA Anderson.

Jaewon R. Choi

Jaewon Royce Choi is a Postdoctoral Research Fellow at Spiegel Research Center at Northwestern University Medill School of Journalism, Media, and Integrated Marketing Communications. He is interested in how digital information technologies shape and influence engagement in media. His research has examined effects of user engagement such as technology adoption, and social implications of technology around issues such as digital inclusion, digital literacy and skills, privacy, and surveillance. He employs various quantitative methods including survey, statistical modeling, and computational social science tools for his research. His work has been published in New Media & Society, International Journal of Communication, Computers in Human Behavior, and Information, Communication & Society. He earned his PhD in 2022 in media studies from the University of Texas at Austin.

Edward C. Malthouse

Edward C. Malthouse is the Erastus Otis Haven Professor of Integrated Marketing Communications and Professor of Industrial Engineering and Management Science at Northwestern University. His is the Research Director for the Spiegel Center for Digital and Database Marketing and a researcher for the Local News Initiative, both at Northwestern University. He is the co-editor of the Journal of Service Research and associate Editor for Frontiers in Big Data-Recommender Systems. He was the co-editor of the Journal of Interactive Marketing between 2005-2011 and has co-edited two special issues for the Journal of Advertising. His research interests center on customer engagement and experiences; digital, social and mobile media; media management; big data; customer relationship management and lifetime value models; recommender systems; and predictive analytics. He earned his PhD in 1995 in statistics focusing on neural networks and machine learning from Northwestern University and completed a post doc at the Kellogg marketing department.