In recent decades, natural language text generation methods have improved for automatic text generation. Also, the recognition and automatic generation of text for personalized persuasion has recently received much attention. The text used to persuade the target Audience has been shown to be very effective in various fields. In this paper, we propose to use the CATGAN framework to generate a text that is classified into levels of persuasion and to target people according to the extent to which that persuasion strategy affects each personality trait. We present a persuasive personalized text generation system that achieves state-of-the-art results in text generation for personal persuasion.