## 1 Introduction  
Over the years, with the great technological advances in the digital world, there has been an increase in the demand for better interactions between subscribers and businesses. Companies risk \"falling behind\" or losing a competitive advantage if they do not keep up with the trends imposed by their subscribers [1]. To maintain the subscribers' interest in their offers, brands, and businesses, organizations must provide personalized experiences. To achieve this level of personalization, brands must know their subscribers. One of the most important channels of marketing communications is email marketing [2, 3, 4]. It consists of sending the best offer or communication to the right person at the right time, based on subscribers profiles. In a broader perspective, any email message sent by a company to a subscriber consists of email marketing [5, 6, 7]. In 2015, a study conducted by direct marketing stated that more than 90% of businesses use email marketing as a manner of direct and efficient communication, which strengthens the Return on Investment (ROI) rates [8]. In 2017, a study conducted by Salesforce [9] stated that one of the channels with the highest growth in recent years was an email with a rate of 83%. In the same year, VentureBeat stated that email was the channel with the highest ROI for marketers, surpassing social networks [10]. For every dollar, email marketing generates 38 dollars in ROI. In another study carried out by HubSpot [11] in 2020, approximately 80% of marketers state that the interactions with the subscribers, by email, have improved compared to previous years. Furthermore, companies, on average, manage to earn 42 dollars for each dollar invested in the advertising sent by email. With the exponential growth of email over the years, broad flows of campaigns are sent and received by subscribers, which reveals itself to be a problem for both companies and subscribers. For companies, it results in the loss of visibility, low opening rates, and consequently, low sales rates. For subscribers, it results in the accumulation of emails in their inboxes, leading subsequently to the elimination of emails and the non-opening, and sometimes, the classification of emails as spam [11]. In a study conducted by HubSpot [12], subscribers only open their email if it has any value to them, determining that relevance is the key to attracting subscribers. Associating this knowledge with the prediction of the best period to send communications, individualized and personalized, companies have better opportunities to conquer the subscriber. Smart systems have been used in several domains, including marketing [13; 14; 15]. In a study conducted by Salesforce in 2017 [9], one of the areas where artificial intelligence would have the greatest impact, with 61%, impact would be in delivering the right message through the right channel, at the right time, and in segmenting subscribers, with 59% impact. In this context, machine learning algorithms allow subscribers to be segmented/organized by their behaviors/profiles, such as [16; 17]: (i) open rates, the percentage of subscribers who interact with the communications received; (ii) click-through rates, the percentage of subscribers who clicked on one or more links in the received email; (iii) the frequency; or (iv) period of interactions with the companies. Based on this information, companies should be able to send their communications on time. Send Frequency Optimization has a major impact on the sending of marketing emails and on the way subscribers react to the campaigns received [18; 19]. Machine learning models, and consequently deep learning models, may handle the following questions [20; 21; 22]. How frequently should we pay attention to each subscriber and send new marketing messages? How frequently should we track leads [23]? Should we initially contact the subscriber? When is the best period of time to send out new marketing messages?