Presentations are effective ways of communicating information, especially in the field of education, but they might not be equally or fully beneficial and persuasive to all users. Each member of the audience might be interested in a particular topic, come from a different background and profession, and have his or her own personality traits. In this conceptual paper, we first describe our persuasive personalization model; the Individualization Pyramid based on Yale Attitude Change Approach. The model consists of the following main sections: selecting contents by applying segmentation, adjusting comprehensibility of the text, tailoring the language of the text to fit with user's personality and recommending content that is associated with user's personal history within the related subjects. We then propose an enhanced version of our previously published presentation builder, which uses users' digital traces such as those on social media to personalize presentation content. Finally, we highlight the available tools and algorithms to assist us with developing the system.