The Role of Artificial Intelligence in Improving the Performance of Digital Marketing Strategies
Keywords:
Artificial intelligence, digital marketing strategy, profitability, competitiveness, Point Estimation Method, Analytic Hierarchy ProcessAbstract
This study examines the effect of artificial intelligence on the performance of digital marketing strategies, with a focus on key components such as sales volume, profitability, competitiveness, customer loyalty, and risk management. The research method is applied and descriptive-survey in nature, and the data were collected through a 35-item questionnaire based on a Likert scale from a statistical population consisting of 50 companies active on the Tehran Stock Exchange. The Analytic Hierarchy Process was used to prioritize the factors, and the Point Estimation Method was employed to model digital marketing risks. The research instrument was designed after its content validity was confirmed by experts and its reliability was found to be acceptable, with Cronbach’s alpha values above 0.70. The findings indicate that the use of artificial intelligence has a significant effect on improving key digital marketing indicators, including an increase in conversion rate, a reduction in customer acquisition cost, and an improvement in return on investment. In addition, artificial intelligence improved performance across different channels, especially email marketing, by increasing email open and click-through rates, and social media marketing, by increasing user engagement. The data analysis showed that artificial intelligence, through optimizing audience targeting and providing personalized content, has the greatest effect on customer loyalty and increased sales. However, its effect on content marketing and SEO was more relative. Overall, the results indicate that artificial intelligence can substantially enhance the performance of digital marketing strategies in the dimensions of sales, profitability, competitiveness, and customer loyalty through complex data analysis and intelligent decision-making.
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Copyright (c) 2025 Mahdi Haji Ali Khamseh (Author); Fatemeh Rabeifar (Corresponding author); Reza Fayazi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
