The Influence of Marketing AI Tools on Customer Behavior and Preference Formation

An Empirical Analysis at Zain Telecommunications, Karbala Branch

Authors

  • Ghaida M. Ali Ezzat College of Administration and Economics, Department of Statistics, University of Karbala, Iraq-Karbala. https://orcid.org/0009-0002-9930-7901
  • Nagham Daikh Abd-Ali College of Administration and Economics, Department of Banking and Financial Sciences, University of Karbala, Iraq-Karbala.
  • Hawra’ Thamir Mahdi Hasan College of Administration and Economics, Department of Banking and Financial Sciences, University of Karbala, Iraq- Karbala. https://orcid.org/0009-0002-7843-7635

DOI:

https://doi.org/10.71207/ijas.v21i86.5036

Keywords:

Marketing AI Tools, Customer Behavior and Preference, Zain Telecommunications

Abstract

     The research analyzed the Marketing AI Tools and their impact on shaping consumer behavior and preferences. It sought to achieve a set of controls, the most important of which is the extent of the researched company's interest in the concepts of artificial marketing intelligence tools, preference, and specific preferences. The search for an innovation remained from (150) groups of individuals working in the research company, and the search continues for a tool as quick tool to access data, and accelerate the formation of the questionnaire, including (the Bach-Cron test for Volkswagen). elastic deviation, contracting on small difference, linear contraction, contracting, T-test, F-test), which was published by the programs (SPSS.19), and one of the most prominent features of it is that the interest in artificial marketing intelligence tools and this is certainly in the company under study in improving communication preferences is very famous, but the most important demands are to display the company’s services easily and conveniently for all our clients very recently to attract and gain the largest possible number of clients with it.

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Author Biographies

Ghaida M. Ali Ezzat, College of Administration and Economics, Department of Statistics, University of Karbala, Iraq-Karbala.

He holds a master's degree in Business Administration (Marketing Management).

Nagham Daikh Abd-Ali, College of Administration and Economics, Department of Banking and Financial Sciences, University of Karbala, Iraq-Karbala.

He holds a Master's degree in Business Administration (Marketing Management) and a PhD in Business Administration.

Hawra’ Thamir Mahdi Hasan, College of Administration and Economics, Department of Banking and Financial Sciences, University of Karbala, Iraq- Karbala.

He holds a master's degree in Business Administration (Marketing Management).

References

1. أحمد, بسمه توفيق, موسى, & تامر محمد. (2023). أثر الذكاء الاصطناعي التسويقي على إدارة علاقات العملاء CRM: بالتطبيق على عملاء الأسواق الإلكترونية في مصر. المجلة العلمية للدراسات والبحوث المالية والتجارية, 4(2), 289-331.

2. Agag, G., Eid, R., Lababdi, H. C., Abdelwahab, M., Aboul-Dahab, S., & Abdo, S. S. (2024). Understanding the impact of national culture differences on customers’ online social shopping behaviours. Journal of Retailing and Consumer Services, 79, 103827.‏

3. Alsammarraie, R. M. (2025). Artificial Intelligence and Digital Transformation in Iraq: Strategic Integration Framework. Journal of Madenat Alelem University College, 17(1), 65-79.‏

4. Amelia, I., Azzahra, Y. N., Abda, A., & Azmi, Z. (2024). Pemanfaatan Artificial Intelligence Dalam Akuntansi: Kajian Literatur Review. Akuntansi, 3(1), 129-140.‏

5. Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation. Journal of Financial Economics, 151, 103745.‏

6. Bajak, M., & Spendel, Ł. (2024). The possibilities of using artificial intelligence in advertising: theory and practice. Zeszyty Naukowe. Organizacja i Zarządzanie/Politechnika Śląska.‏

7. Chaffey, D. (2022). Global social media statistics research summary 2022. Smart Insights.‏

8. Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188.‏

9. Cui, L., Wang, Y., Chen, W., Wen, W., & Han, M. S. (2021). Predicting determinants of consumers' purchase motivation for electric vehicles: An application of Maslow's hierarchy of needs model. Energy Policy, 151, 112167.‏

10. Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42.‏

11. Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.‏

12. Demirkan, H., Spohrer, J. C., & Welser, J. J. (2016). Digital Innovation and Strategic Transformation. In IT Professional (Vol. 18, Issue 6, pp. 14–18). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/mitp.2016.115

13. Di Gaetano, S., & Diliberto, P. (2018). Chatbots and conversational interfaces: Three domains of use. In Fifth International Workshop on Cultures of Participation in the Digital Age, Castiglione della Pescaia, Italy (Vol. 2101, pp. 62-70).‏

14. Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897-904.

15. Fagella, D. (2018). Artificial intelligence in marketing and advertising – 5 examples of real traction.

16. Filieri, R., & Mariani, M. (2021). The role of cultural values in consumers' evaluation of online review helpfulness: a big data approach. International Marketing Review, 38(6), 1267-1288.‏

17. Fishbein, M. & Ajzen, I. (1975). Predicting and understanding consumer behavior: Attitude-behavior correspondence. In Ajzen, I. & Fishbein, M. (eds.). Understanding Attitudes and Predicting Social Behavior (pp. 148-172). Englewood Cliffs, NJ: Prentice Hall.

18. FOLLAD, M., AKPINAR, A., & TİLTAY, M. A. (2021). Mobile Marketing: Current State and Future Research Directions.‏

19. Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International journal of information management, 35(2), 137-144.‏

20. Gupta, O. P., Gaurav, R., & Jaiswal, M. K. Understanding the Decision-Making Process in Consumer Buying Behaviour: An Insight.‏

21. Haque, A., Akther, N., Khan, I., Agarwal, K., & Uddin, N. (2024, October). Artificial Intelligence in Retail Marketing: Research Agenda Based on Bibliometric Reflection and Content Analysis (2000–2023). In Informatics (Vol. 11, No. 4, p. 74). MDPI.

22. Johnson, J. (2020). Artificial intelligence: A threat to strategic stability. Strategic studies quarterly, 14(1), 16-39.‏

23. Kotler, P., Keller, K. L., Ancarani, F., & Costabile, M. (2014). Marketing management 14/e. pearson.‏

24. Kumar, V., Dixit, A., Javalgi, R. R. G., & Dass, M. (2016). Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing. Journal of the Academy of Marketing Science, 44(1), 24-45.‏

25. Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96.

26. Leonov, Y., Nakonechnyi, O., Khalimanenko, V., Nikolaiko, H., & Heraimovych, V. (2023). Analysis of the influence of psychological factors on consumer behavior and the decision-making process.‏

27. Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases. Marketing Science, 38(6), 937–947.

28. Mateja, A., Subocz, D., Stępień-Słodkowska, M., & Nermend, M. (2024, October). Cognitive Load and Online Customer Decisions: The Role of Visual Perception, Memory, and Brain Activity. In European Conference on Artificial Intelligence (pp. 90-101). Cham: Springer Nature Switzerland.‏

29. Ng, I. C., & Wakenshaw, S. Y. (2017). The Internet-of-Things: Review and research directions. International Journal of Research in Marketing, 34(1), 3-21.‏

30. Petrescu, M., Krishen, A. S., Kachen, S., & Gironda, J. T. (2022). AI-based innovation in B2B marketing: An interdisciplinary framework incorporating academic and practitioner perspectives. Industrial Marketing Management, 103, 61-72.‏

31. Prahalad, C. K., & Ramaswamy, V. (2004). Co-creation experiences: The next practice in value creation. Journal of Interactive Marketing, 18(3), 5-14.

32. Riverso, R., Altamura, C., & La Barbera, F. (2023). Consumer intention to buy electric cars: Integrating uncertainty in the Theory of Planned Behavior. Sustainability, 15(11), 8548.‏

33. Rosenberg, M.J. and Hovland, C.I. (1960) Cognitive, Affective and Behavioral Components of Attitudes. In: Rosenberg, M.J. and Hovland, C.I., Eds., Attitude Organization and Change: An Analysis of Consistency among Attitude Components, Yale University Press, New Haven.

34. Schrotenboer, D. W. (2019). The impact of artificial intelligence along the customer journey: a systematic literature review.‏

35. Shabbir, J., & Rehman, K. U. (2013). Impact of Perceptual Dimensions and Behavioral dimension on brand equity in Pakistan. Information Management and Business Review, 5(7), 347.‏

36. Shahbee, T., Danish, M., & Zehri, A. W. (2023). Impact of Social and Personal factors on Consumer Purchase Intention using Attitude as a mediator. Research Journal for Societal Issues, 5(3), 345-368.‏

37. Shaikh, S. (2022). Internet of things: designing digital eco-systems for competitive tourism related micro and small enterprises in Pakistan. In Technology Application in Tourism in Asia: Innovations, Theories and Practices (pp. 349-365). Singapore: Springer Nature Singapore.‏

38. Sinulingga, S. P. B., & Nasution, M. I. P. (2024). Analysis Of Challenges And Opportunities In The Development Of Information And Communication Technology In The Digital Era: Future Perspective. Jurnal Ilmiah Ekonomi Dan Manajemen, 2(12), 25-35.‏

39. Sterne, J. (2017). Artificial intelligence for marketing: practical applications. John Wiley & Sons.‏

40. Storbacka, K., Brodie, R. J., Böhmann, T., Maglio, P. P., & Nenonen, S. (2016). Actor engagement as a microfoundation for value co-creation. Journal of business research, 69(8), 3008-3017.‏

41. Syam, N., & Sharma, A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial marketing management, 69, 135-146.‏

42. Tulcanaza-Prieto, A. B., Cortez-Ordoñez, A., & Lee, C. W. (2023). Influence of customer perception factors on AI-enabled customer experience in the Ecuadorian banking environment. Sustainability, 15(16), 12441.‏

43. Van Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017). Domo arigato Mr. Roboto: Emergence of automated social presence in organizational frontlines and customers’ service experiences. Journal of service research, 20(1), 43-58.‏

44. Verhoef, P. C., Reinartz, W. J., & Krafft, M. (2010). Customer engagement as a new perspective in customer management. Journal of service research, 13(3), 247-252.

45. Wahyuni, A. C., Masnita, Y., & Kurniawati, K. (2025). SOCIAL LEARNING THEORY IN CUSTOMER ENGAGEMENT TO INCREASE IMPULSIVE BUYING BEHAVIOR. Journal of Management: Small and Medium Enterprises (SMEs), 18(1), 613-627.‏

46. Wang, S., Guo, Y., & Ding, H. (2025). The Impact of Emotion on Consumer Behavior. Advances in Economics, Management and Political Sciences, 196(1), 29–38. https://doi.org/10.54254/2754-1169/2025.BJ24755

47. Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121.

48. Yang, S., Isa, S. M., Wu, H., Thurasamy, R., Fang, X., Fan, Y., & Liu, D. (2022). Effects of stores’ environmental components on Chinese consumers’ emotions and intentions to purchase luxury brands: Integrating partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis approaches. Frontiers in Psychology, 13, 840413.‏

49. Zain Iraq. (n.d.). AI and Cybersecurity.

50. Zain. (2019). Commercial and Customer Experience.

51. Zain. (2025, May 5). Zain's internal innovation program 'ZAINIAC' invests in Actly, an AI startup delivering personalized customer experiences through AI Agents.

52. Zeelenberg, R., Wagenmakers, E. J., & Rotteveel, M. (2006). The impact of emotion on perception: Bias or enhanced processing?. Psychological Science, 17(4), 287-291.‏

المخطط

Published

2025-12-23

How to Cite

M. Ali Ezzat, G., Daikh Abd-Ali, N., & Thamir Mahdi Hasan, H. (2025). The Influence of Marketing AI Tools on Customer Behavior and Preference Formation: An Empirical Analysis at Zain Telecommunications, Karbala Branch. Iraqi Journal for Administrative Sciences, 21(86), 376–400. https://doi.org/10.71207/ijas.v21i86.5036