Abstract
E-mail marketing is one of the main channels of communication with existing and potential customers. The Open Rate metric is as one of the primary indicators of email campaign success. There are many features of e-mail communication affecting the behavior of individual recipients. Understanding and properly setting these features imply the success of email marketing campaigns. One of these features is the time to send the e-mail. In this paper, we present a methodology for predicting suitable email sending time. Analyzing the available data collected from e-mail communications between companies and customers creates a space for applying data mining methods to data. The proposed methodology for the generation of prediction models to determine the optimal time to send an email has been implemented and evaluated on a real dataset with very promising results.
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