An e-mail response automation system (ERA) tries to identify specific use cases within the body of an e-mail message. This is achieved with the help of artificial intelligence. Correctly classified e-mails are then forwarded to a process automation system, which takes care of all required system queries. Finally, the ERA bot creates a response template that is presented to an employee to guarantee service quality. In the thesis, an analysis of e-mail conversations highlighted where such an ERA bot could support employees.

The author conducted a literature review of relevant topics so that the reader could get an understanding of the involved technology. As a next step, the approach and pricing models of two ERA providers were described and compared. Later, a quantitative analysis gave insight into the most frequent business cases. Four business cases were subsequently addressed in a qualitative analysis, in which the author assessed 50 e-mail conversations each to identify customer intentions and the involved information. Lastly, use case formulations and an estimation of cost savings were created.

The thesis compared two providers of ERA solutions and highlighted specific business scenarios in which customers provide sufficient information for ERA. Further, the use case formulations gave an orientation where such automation could be considered and how a bot would have to proceed. Finally, the management used the main insights and estimation of the thesis as a basis for a project decision.