Computing advertising intelligent computing and push based on artificial intelligence in the big data era

• Published in: Heliyon Vol. 10; no. 17; p. e37252
• Main Author: Shan, Lin
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.09.2024; Elsevier
• Subjects: Advertising push; Artificial intelligence; Big data; Computational advertising; Internet; profitability; Return on investment; tourism; Computational advertising; Big data; Return on investment; Artificial intelligence; Advertising push
• DOI: 10.1016/j.heliyon.2024.e37252
• ISSN: 2405-8440

In the era of big data, intelligent computation and precise targeting of advertisements rely on artificial intelligence (AI) technology to enhance advertising effectiveness and user experience. As advertising media shift from traditional outlets to the internet and mobile devices, manually filtering and targeting advertisements has become increasingly ineffective due to the vast amount of information and user groups. Consequently, AI-based advertisement computation and targeting technologies have emerged. This paper explores how modern technologies and AI applications can be used to achieve intelligent computation, filtering, and targeting of advertisements, thereby improving ad effectiveness and profitability. The study optimizes ad targeting effectiveness and increases return on investment (ROI) by comparing ad campaigns between Group A, which did not use ad targeting algorithms, and Group B, which employed AI-based targeting algorithms. The experimental results show that the average ROI for tourism, shopping, and rental ads in Group A were 153.03 %, 232.32 %, and 192.57 %, respectively, while Group B's average ROI were 173.96 %, 288.74 %, and 216.12 %. These results indicate that AI-based ad targeting algorithms can significantly improve the ROI of ad campaigns compared to non-algorithmic approaches, suggesting that ad targeting algorithms can help advertisers achieve higher profits.