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Educational marketing management helps higher educational institutions (HEIs) discover student demands and improve competition. Despite the significance of educational marketing, HEI adopt the same corporate techniques regardless of their area. To adhere to the changing context of the digital era, HEI must update and improve their marketing tactics based on emerging consumer trends. This study examines the correlation between revenue growth and psychology. It proposes a hybrid approach that uses deep learning's topology to forecast preferences. Employ a hash technique to accurately market to modern age users by analyzing their conduct, knowledge, and recommending relevant resources. This study's framework outperforms five other algorithms in multifaceted recognition evaluation, with an accuracy of 79.7%, recall percentage of 77.5%, F1 of 0.79, and error readings of approximately 0.19 after epoch iteration. The framework is highly useful. Every user's portrait framework is then generated. Portrait enhancement yielded 7 marketing approaches with impressive results, ranging from 70% to 83%. Additionally, the financial position was good. An smart and effective dynamic planning assistance is offered for HEI by the final framework's acceptable design and outstanding data efficiency.
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Reddy et al. (2025) studied this question.