@inproceedings{BenderFabianHauptetal.2018,
  author    = {Bender, Benedict and Fabian, Benjamin and Haupt, Johannes and Neumann, Tom},
  title     = {Track and Treat},
  series = {Twenty-Sixth European Conference on Information Systems (ECIS 2018)},
  booktitle = {Twenty-Sixth European Conference on Information Systems (ECIS 2018)},
  pages     = {14},
  year      = {2018},
  abstract  = {E-Mail tracking mechanisms gather information on individual recipients' reading behavior. Previous studies show that e-mail newsletters commonly include tracking elements. However, prior work does not examine the degree to which e-mail senders actually employ gathered user information. The paper closes this research gap by means of an experimental study to clarify the use of tracking-based infor- mation. To that end, twelve mail accounts are created, each of which subscribes to a pre-defined set of newsletters from companies based in Germany, the UK, and the USA. Systematically varying e-mail reading patterns across accounts, each account simulates a different type of user with individual read- ing behavior. Assuming senders to track e-mail reading habits, we expect changes in mailer behavior. The analysis confirms the prominence of tracking in that over 92\% of the newsletter e-mails contain tracking images. For 13 out of 44 senders an adjustment of communication policy in response to user reading behavior is observed. Observed effects include sending newsletters at different times, adapting advertised products to match the users' IT environment, increased or decreased mailing frequency, and mobile-specific adjustments. Regarding legal issues, not all companies that adapt the mail-sending behavior state the usage of such mechanisms in their privacy policy.},
  language  = {en}
}
@inproceedings{FabianBenderWeimann2015,
  author    = {Fabian, Benjamin and Bender, Benedict and Weimann, Lars},
  title     = {E-Mail tracking in online marketing},
  series = {Proceedings of the 12th International Conference on Wirtschaftsinformatik},
  booktitle = {Proceedings of the 12th International Conference on Wirtschaftsinformatik},
  number    = {74},
  publisher = {Associations for Information Systems AIS},
  address   = {Atlanta},
  isbn      = {978-3-00-049184-9},
  pages     = {15},
  year      = {2015},
  abstract  = {E-Mail tracking uses personalized links and pictures for gathering information on user behavior, for example, where, when, on what kind of device, and how often an e-mail has been read. This information can be very useful for marketing purposes. On the other hand, privacy and security requirements of customers could be violated by tracking. This paper examines how e-mail tracking works, how it can be detected automatically, and to what extent it is used in German e-commerce. We develop a detection model and software tool in order to collect and analyze more than 600 newsletter e-mails from companies of several different industries. The results show that the usage of e-mail tracking in Germany is prevalent but also varies depending on the industry.},
  language  = {en}
}
@inproceedings{BenderFabianLessmannetal.2016,
  author    = {Bender, Benedict and Fabian, Benjamin and Lessmann, Stefan and Haupt, Johannes},
  title     = {E-Mail Tracking},
  series = {Proceedings of the 37th International Conference on Information Systems (ICIS)},
  booktitle = {Proceedings of the 37th International Conference on Information Systems (ICIS)},
  pages     = {19},
  year      = {2016},
  abstract  = {E-mail advertisement, as one instrument in the marketing mix, allows companies to collect fine-grained behavioural data about individual users' e-mail reading habits realised through sophisticated tracking mechanisms. Such tracking can be harmful for user privacy and security. This problem is especially severe since e-mail tracking techniques gather data without user consent. Striving to increase privacy and security in e-mail communication, the paper makes three contributions. First, a large database of newsletter e-mails is developed. This data facilitates investigating the prevalence of e- mail tracking among 300 global enterprises from Germany, the United Kingdom and the United States. Second, countermeasures are developed for automatically identifying and blocking e-mail tracking mechanisms without impeding the user experience. The approach consists of identifying important tracking descriptors and creating a neural network-based detection model. Last, the effectiveness of the proposed approach is established by means of empirical experimentation. The results suggest a classification accuracy of 99.99\%.},
  language  = {en}
}