Journal of Advertising and Sales Management

Journal of Advertising and Sales Management

Investigating the Effects of Artificial Intelligence on the Optimization of Marketing Processes

Authors
Elahe Asadolahidehkordi 1
Mohammadtaha Esmaeilzadeh Ashini 2
1 Assistant Professor, Department of Business Administration, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
2 MSc. Student in Business Management, Department of Business Management, Faculty of Islamic Studies and Management, Imam Sadegh University, Tehran, Iran
10.22034/asm.2025.2047701.3320
Abstract
This study examines the role of Artificial Intelligence (AI) in optimizing marketing processes. The goal is to analyze the effects of AI on cost reduction, improving decision-making accuracy, enhancing customer experience, and strengthening the competitive capabilities of companies. The research approach is mixed (qualitative and quantitative). In the qualitative section, data were collected through semi-structured interviews with 13 experts in the fields of marketing and AI, and analyzed using thematic analysis, leading to the identification of 9 main themes and 57 sub-themes. In the quantitative section, the Analytical Hierarchy Process (AHP) was used to prioritize the main themes, and data were collected through pairwise comparison questionnaires from 8 experts in marketing and information technology and analyzed using specialized software.
The findings revealed that AI has significant impacts on marketing processes. The main effects identified include reducing operational and advertising costs, decreasing human error, enhancing decision-making accuracy, improving marketing operation speed, and enhancing customer experience. Reducing human error was identified as the most important effect, while improving resource management was the least significant. AI also helps personalize customer interactions and makes marketing processes more targeted, thus increasing the competitive advantage of companies, especially in international markets.
Effective use of AI requires the development of precise strategies, staff training, and attention to customer privacy. Additionally, in international markets, it is essential to adapt AI-based marketing strategies to cultural differences and local needs. This study emphasizes the importance of smart AI usage to enhance competitiveness and customer satisfaction.
Keywords
Artificial Intelligence
Effects of Artificial Intelligence
Smart Marketing
Marketing Processes
Subjects
  1. ترابی، محمدامین، عباسیان، عزت‌الله، و میلانی، سیدمحمدصادق. (1403). بازاریابی هوشمند با استفاده از چت جی‌پی‌تی. مدیریت بازاریابی هوشمند، 5(1).
  2. جهان‌فر، حامد، و الهی خراسانی، اکبر. (1402). هوش مصنوعی در بازاریابی: مرور سیستماتیک و جهت تحقیقات آینده. مدیریت بازاریابی هوشمند، 4(4)، 32-51.
  3. زارعی، قاسم، محمدخانی، رحیم، و فتحی، هاجر. (1403). بررسی و شناسایی پیامدهای کاربرد هوش مصنوعی در بازاریابی. پژوهش‌های مدیریت در ایران، 28(2)، 1-31.
  4. کاظمی سراسکانرود، زهرا، و صفری، محمد. (1402). طراحی الگوی فرایند بازاریابی مبتنی بر هوش مصنوعی: کاربست راهبرد مرور نظام‌مند. بررسی‌های بازرگانی، 21(123)، 109-126. https://doi.org/10.22034/bs.2023.1999484.2765
  5. یزدان پرست، سید مرتضی، جامی پور، مونا، و جعفری، سید محمدباقر. (1401). شناسایی و اولویت‌بندی کاربردهای هوش مصنوعی در بازاریابی برخط. کاوش‌های مدیریت بازرگانی, 14(28), 103-137.
  6. Alammal, A. H., & Al Mubarak, M. (2023). Artificial intelligence in marketing: Concerns and solutions. In M. Al Mubarak & A. Hamdan (Eds.), Technological sustainability and business competitive advantage. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-031-35525-7_7
  7. Alamsyah, A., & Syahrir, S. (2024). Taxonomy on Blockchain-Based Technology in the Financial Industry: Drivers, Applications, Benefits, and Threats. In Blockchain and Smart-Contract Technologies for Innovative Applications (pp. 91-129). Springer, Cham. https://www.researchgate.net/publication/378629625_A_Taxonomy_on_Blockchain-Based_Technology_in_the_Financial_Industry_Drivers_Applications_Benefits_and_Threats
  8. Arora, S., & Thota, S. R. (2024). Using Artificial Intelligence with Big Data Analytics for Targeted Marketing Campaigns. no. June.‏
  9. Callejas, J. F., & Lis-Gutiérrez, J. P. (2024). Applications of artificial intelligence in marketing: An approach from the patent record. In Y. Farhaoui (Ed.), Artificial intelligence, big data, IOT and blockchain in healthcare: From concepts to applications (Vol. 5, pp. 567-578). Springer. https://doi.org/10.1007/978-3-031-65014-7_45
  10. Chaffey, D., & Ellis-Chadwick, F. (2019). Digital marketing: Strategy, implementation and practice (7th ed.). Pearson.
  11. Chaubey, G., Gavhane, P. R., Bisen, D., & et al. (2023). Customer purchasing behavior prediction using machine learning classification techniques. Journal of Ambient Intelligence and Humanized Computing, 14(12), 16133–16157. https://doi.org/10.1007/s12652-022-03837-6
  12. Chintalapati, S., & Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68. https://doi.org/10.1177/14707853211018428
  13. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard business review, 96(1), 108-116.‏
  14. Davenport, T., Guha, A., Grewal, D., & others. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0
  15. De Mauro, A., Sestino, A., & Bacconi, A. (2022). Machine learning and artificial intelligence use in marketing: a general taxonomy. Italian Journal of Marketing, 2022(4), 439–457. https://doi.org/10.1007/s43039-022-00057-w
  16. Dhawas, P., Bondade, A., Patil, S., Khandare, K. S., & Salunkhe, R. V. (2024). Intelligent automation in marketing. In Hyperautomation in business and society (pp. 66-88). IGI Global. https://doi.org/10.4018/979-8-3693-3354-9.ch003
  17. George, S., Sajan, B., Sasikala, B., Sopna, P., Umamaheswari, M., & Dhinakaran, D. (2024). Role of artificial intelligence in marketing strategies and performance. Migration Letters, 21(4), 1589–1599.
  18. Grewal, D. S. (2014). A critical conceptual analysis of definitions of artificial intelligence as applicable to computer engineering. IOSR Journal of Computer Engineering, 16(2), 9-13.‏
  19. Gujar, V. (2024). New Age Marketing: AI Personalization Strategies in Digital World. Available at ResearchGate.
  20. Hannig, U. (2023). Automation of Repetitive Processes in Marketing and Sales. In Marketing and Sales Automation: Basics, Implementation, and Applications (pp. 7-18). Cham: Springer International Publishing.‏
  21. Hassan, A., Mohammed, F. A., & Seyadi, A. Y. (2024). Artificial intelligence applications for marketing. In A. M. A. Musleh Al-Sartawi & A. I. Nour (Eds.), Artificial intelligence and economic sustainability in the era of industrial revolution 5.0. Studies in Systems, Decision and Control (Vol. 528, pp. 579–594). Springer, Cham. https://doi.org/10.1007/978-3-031-56586-1_43
  22. Hauser, J. R., Li, Z., & Mao, C. (2023). Artificial Intelligence and user-generated data are transforming how firms come to understand customer needs. In Artificial Intelligence in Marketing (pp. 147-167). Emerald Publishing Limited.‏ https://doi.org/10.1108/S1548-643520230000020007
  23. Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9
  24. Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024). Leveraging artificial intelligence for personalized marketing campaigns to improve conversion rates. International Journal of Engineering Research and Development, 20(8), 253-270.
  25. Jacques,B., Eric,H., James,M., Jonathan,W. (June 2017), ‘Artificial Intelligence: The Next DigitalFrontier’,McKinseyGlobalInstitute,availableat http://dln.jaipuria.ac.in:8080/jspui/bitstream/123456789/14268/1/MGI-artificial-intelligence-discussion-paper.pdf
  26. Jiang, J., & Wang, X. (2024). Animation scene generation based on deep learning of CAD data. https://cad-journal.net/files/vol_21/CAD_21(S19)_2024_1-16.pdf
  27. Joseph, C. (2024). International business expansion strategies: Entering new markets. Estaga Journal of Philosophy, Arts and Humanities, 1(2).
  28. Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37-50.‏ https://doi.org/10.1016/j.bushor.2019.09.003
  29. Kedi, W. E., Ejimuda, C., Idemudia, C., & Ijomah, T. I. (2024). AI software for personalized marketing automation in SMEs: Enhancing customer experience and sales. World Journal of Advanced Research and Reviews, 23(1), 1981–1990. https://doi.org/10.30574/wjarr.2024.23.1.2159
  30. Kotler, P., & Keller, K. L. (2016). Marketing management (15th ed.). Pearson.
  31. Lakshmipriyanka , M.,Harihararao. , M. Prasanna. , Y. Deepika.(2023).A Study on Artificial Intelligence in Marketing.International Journal for Multidisciplinary Research (IJFMR),E-ISSN: 2582-2160. DOI https://doi.org/gsct4b
  32. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of marketing, 80(6), 69-96.‏ https://doi.org/10.1509/jm.15.0420
  33. Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911-926. https://doi.org/10.1016/j.jbusres.2020.11.001
  34. Matcov, A. (2024). Explainable AI in credit risk assessment for external customers (Bachelor's thesis, University of Twente). https://purl.utwente.nl/essays/98204
  35. McAfee, A., & Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. WW Norton & Company.‏
  36. McLaughlin, D. (2024). Remarks on Blockchain and distributed ledger technology in financial market infrastructures. Available at SSRN 4745315.
  37. Njoku, K. C. (2024). Artificial intelligence (AI) and business practices: Insights from marketing firms in Owerri. African Journal of Social and Behavioural Sciences, 14(6).
  38. Okeleke, P. A., Ajiga, D., Folorunsho, S. O., & Ezeigweneme, C. (2024). Predictive analytics for market trends using AI: A study in consumer behavior. International Journal of Engineering Research Updates, 7(1), 36–49. https://doi.org/10.53430/ijeru.2024.7.1.0032
  39. Patil, D. (2024). Artificial intelligence for personalized marketing and consumer behaviour analysis: Enhancing engagement and conversion rates.
  40. Perifanis, N. A., & Kitsios, F. (2023). Investigating the Influence of Artificial Intelligence on Business Value in the Digital Era of Strategy: A Literature Review. Information 2023, 14 (2), 85.‏ https://doi.org/10.3390/info14020085
  41. Philip, K., Hermawan, K., & Iwan, S. (2017). Marketing 4.0: Moving from Traditional to Digital.‏
  42. Rahman, J., Raihan, A., Tanchangya, T., & Ridwan, M. (2024). Optimizing the digital marketing landscape: A comprehensive exploration of artificial intelligence (AI) technologies, applications, advantages, and challenges. Future Frontiers, 2(2). https://doi.org/10.59429/ff.v2i2.6549
  43. Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach. Pearson Education.
  44. Rust, R. T. (2020). The future of marketing. International Journal of Research in Marketing, 37(1), 15-26.‏ https://doi.org/10.1016/j.ijresmar.2019.08.002
  45. Shaik, M. (2023). Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research, 2(3), 993–1004. https://doi.org/10.55927/eajmr.v2i3.3112
  46. Simmons, A. B., & Chappell, S. G. (1988). Artificial intelligence-definition and practice. IEEE journal of oceanic engineering, 13(2), 14-42.‏
  47. Sodiq Odetunde ,B ., Opeyemi Abayomi ,O ., Tolulope Esther, E ., & Damilola O. International Journal of Management & Entrepreneurship Research P-ISSN: 2664-3588, E-ISSN: 2664-3596 Volume 6, Issue 3, P.No.936-949, March 2024 DOI:10.51594/ijmer.v6i3.964
  48. Suprunenko, S., Pishenina, T., Pitel, N., Voronkova, A., & Riabovolyk, T. (2024). Analysis of the Impact of Globalization Trends in the Digital Economy on Business Management and Administration Systems of Enterprises. Futurity Economics&Law, 4(2), 131-147.‏ https://doi.org/10.57125/FEL.2024.06.25.08
  49. Thaduri, U. R. (2020). Decision Intelligence in Business: A Tool for Quick and Accurate Marketing Analysis. Asian Business Review, 10(3), 193-200.‏
  50. Thiraviyam, T. (2018). Artificial intelligence marketing.
  51. Verma, S., Sharma, R., Deb, S., & Maitra, D. (2020). Artificial intelligence in marketing: Systematic review and future research direction. Journal of Innovation & Knowledge, 6(1), 100002. https://doi.org/10.1016/j.jjimei.2020.100002
  52. Vinchhi DEVANG & Shroff CHINTAN & Tanna GUNJAN & Rai KRUPA, 2019. "Applications of Artificial Intelligence in Marketing," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 28-36. https://doi.org/10.35219/eai158404094
  53. Wang, P. (2019). On defining artificial intelligence. Journal of Artificial General Intelligence. Retrieved from sciendo.com.
  54. Yusuf, S. O., Durodola, R. L., Ocran, G., Abubakar, J. E., Echere, A. Z., & Paul-Adeleye, A. H. (2024). Challenges and opportunities in AI and digital transformation for SMEs: A cross-continental perspective. World Journal of Advanced Research and Reviews, 23(3), 668-678.‏
  55. Ziakis, C., & Vlachopoulou, M. (2023). Artificial Intelligence in Digital Marketing: Insights from a Comprehensive Review. Information, 14(12), 664. https://doi.org/10.3390/info14120664