This paper aims to consider the role of AI in corporate and marketing communication and the potential of AI in improving the way organizations engage with their customers. The research employing both qualitative and quantitative research tools, using interviews, focus group discussions, and online self-administered questionnaires, and secondary data to offer a holistic assessment of AI-supported intervention approaches. In the current study, thematic and content analysis were used to understand the conceptions from the marketing professionals’ and consumers’ contributions While quantitative data was analyzed using descriptive statistics, regression analysis, and AI algorithms for the purpose of the predictive models. Some of the best insights show that customer experience is up by 35% and brand performance and personalization are greatly enhanced. The regression analysis showed that personalization has a positive correlation with the consumer engagement with R2 = 0.78, and suggested that increased degree of personalization leads to increased consumer engagement. Furthermore, the result indicates that the data used in predictive modeling has been forecasted with a 90% accuracy if consumer behavior, with classification having a 75% accuracy and clustering having an 82% accuracy. These findings imply that AI-based plans play a major role in improving marketing communication and brand value in the current market environment.

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Navigating the Digital Era: Integrating AI-Driven Strategies in Corporate and Marketing Communications for Enhanced Customer Engagement

  • Hind Al-Ahmed,
  • Khaled Alshaketheep,
  • Ahmad Mansour,
  • Ahmad AlHamad,
  • Muhammad Alshurideh,
  • Imad Al Zeer,
  • Arafat Deeb

摘要

This paper aims to consider the role of AI in corporate and marketing communication and the potential of AI in improving the way organizations engage with their customers. The research employing both qualitative and quantitative research tools, using interviews, focus group discussions, and online self-administered questionnaires, and secondary data to offer a holistic assessment of AI-supported intervention approaches. In the current study, thematic and content analysis were used to understand the conceptions from the marketing professionals’ and consumers’ contributions While quantitative data was analyzed using descriptive statistics, regression analysis, and AI algorithms for the purpose of the predictive models. Some of the best insights show that customer experience is up by 35% and brand performance and personalization are greatly enhanced. The regression analysis showed that personalization has a positive correlation with the consumer engagement with R2 = 0.78, and suggested that increased degree of personalization leads to increased consumer engagement. Furthermore, the result indicates that the data used in predictive modeling has been forecasted with a 90% accuracy if consumer behavior, with classification having a 75% accuracy and clustering having an 82% accuracy. These findings imply that AI-based plans play a major role in improving marketing communication and brand value in the current market environment.