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The Future of Marketing: The Transformative Power of Artificial Intelligence

Yıl 2024, Cilt: 8 Sayı: 15, 1 - 19, 29.02.2024
https://doi.org/10.29064/ijma.1412272

Öz

This research offers a rich narrative explaining this multifaceted relationship by exploring the transformative impact of Artificial Intelligence (AI) on marketing by adopting a qualitative descriptive approach for in-depth exploration. The findings reveal profound implications for customer engagement, market strategy, and ethical considerations. The multifaceted integration of AI into marketing enables customer personalization and increases brand loyalty. Predictive analytics enable businesses to develop proactive strategies aligned with future market dynamics. Despite its advantages, ethical considerations surrounding data privacy and consumer consent require AI to be used responsibly and transparently. Integrated augmented reality, virtual reality, predictive customer journeys, and the Internet of Things that transform marketing dynamics must be harnessed to balance ethical concerns. A comprehensive resource for academic researchers and industry professionals, this work provides a clear roadmap for organizations to effectively leverage AI in their marketing operations in an environment of increasing reliance on digital platforms and expanding data availability.

Kaynakça

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  • Alawneh, Y. J., Al-Momani, T., Salman, F. N., Al-Ahmad, S. D., Kaddumi, T. A., & Al-Dlalah, M. (2023). A Detailed study analysis of artificial intelligence implementation in social media applications. 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 1191–1194. https://doi.org/10.1109/ICACITE57410.2023.10182840
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  • Ayanouz, S., Abdelhakim, B. A., & Benhmed, M. (2020). A smart chatbot architecture based NLP and machine learning for health care assistance. Proceedings of the 3rd International Conference on Networking, Information Systems & Security, 1–6. https://doi.org/10.1145/3386723.3387897
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The Future of Marketing: The Transformative Power of Artificial Intelligence

Yıl 2024, Cilt: 8 Sayı: 15, 1 - 19, 29.02.2024
https://doi.org/10.29064/ijma.1412272

Öz

This research offers a rich narrative explaining this multifaceted relationship by exploring the transformative impact of Artificial Intelligence (AI) on marketing by adopting a qualitative descriptive approach for in-depth exploration. The findings reveal profound implications for customer engagement, market strategy, and ethical considerations. The multifaceted integration of AI into marketing enables customer personalization and increases brand loyalty. Predictive analytics enable businesses to develop proactive strategies aligned with future market dynamics. Despite its advantages, ethical considerations surrounding data privacy and consumer consent require AI to be used responsibly and transparently. Integrated augmented reality, virtual reality, predictive customer journeys, and the Internet of Things that transform marketing dynamics must be harnessed to balance ethical concerns. A comprehensive resource for academic researchers and industry professionals, this work provides a clear roadmap for organizations to effectively leverage AI in their marketing operations in an environment of increasing reliance on digital platforms and expanding data availability.

Kaynakça

  • Abakouy, R., Ennaimi, E. M., Haddadi, A. E., & Lotfi, E. (2019). Data-driven marketing: How machine learning will improve decision-making for marketers. Proceedings of the 4th International Conference on Smart City Applications, 1–5. https://doi.org/10.1145/3368756.3369024
  • Agarwal, S., Agarwal, B., & Gupta, R. (2022). Chatbots and virtual assistants: A bibliometric analysis. Library Hi Tech, 40(4), 1013–1030. https://doi.org/10.1108/LHT-09-2021-0330
  • Agrawal, A. K., Gans, J., & Goldfarb, A. (2019). The Economics of Artificial Intelligence: An Agenda. 439–462.
  • Ahmed, A. A. A., Agarwal, S., Kurniawan, Im. G. A., Anantadjaya, S. P. D., & Krishnan, C. (2022). Business boosting through sentiment analysis using the Artificial Intelligence approach. International Journal of System Assurance Engineering and Management, 13(1), 699–709. https://doi.org/10.1007/s13198-021-01594-x
  • Alawneh, Y. J., Al-Momani, T., Salman, F. N., Al-Ahmad, S. D., Kaddumi, T. A., & Al-Dlalah, M. (2023). A Detailed study analysis of artificial intelligence implementation in social media applications. 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 1191–1194. https://doi.org/10.1109/ICACITE57410.2023.10182840
  • Alzahrani, H. (2016). Artificial intelligence and customer communication. Global Journal of Computer Science and Technology, 16(1).
  • Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548
  • Araújo, T., & Casais, B. (2020). Customer acceptance of shopping-assistant chatbots. In Á. Rocha, J. L. Reis, M. K. Peter, & Z. Bogdanović (Eds.), Marketing and Smart Technologies (pp. 278–287). Springer. https://doi.org/10.1007/978-981-15-1564-4_26
  • Ayanouz, S., Abdelhakim, B. A., & Benhmed, M. (2020). A smart chatbot architecture based NLP and machine learning for health care assistance. Proceedings of the 3rd International Conference on Networking, Information Systems & Security, 1–6. https://doi.org/10.1145/3386723.3387897
  • Bag, S., Gupta, S., Kumar, A., & Sivarajah, U. (2021). An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance. Industrial Marketing Management, 92, 178–189. https://doi.org/10.1016/j.indmarman.2020.12.001
  • Bhardwaj, K. (2021). AI for Data Driven Digital Marketing [Thesis, Delhi Technological University]. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18493
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  • Keskinbora, K. H. (2019). Medical ethics considerations on artificial intelligence. Journal of Clinical Neuroscience, 64, 277–282. https://doi.org/10.1016/j.jocn.2019.03.001
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  • Liu, X., Shin, H., & Burns, A. C. (2021). Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing. Journal of Business Research, 125, 815–826. https://doi.org/10.1016/j.jbusres.2019.04.042
  • Liu, Y., Alzahrani, I. R., Jaleel, R. A., & Sulaie, S. A. (2023). An efficient smart data mining framework based cloud internet of things for developing artificial intelligence of marketing information analysis. Information Processing & Management, 60(1), 103121. https://doi.org/10.1016/j.ipm.2022.103121
  • Liu, Y., & Chen, W. (2021). Optimization of brand marketing strategy of intelligent technology under the background of artificial intelligence. Mobile Information Systems, 2021, e9507917. https://doi.org/10.1155/2021/9507917
  • Liu, Y., & Li, J. (2022). Brand marketing decision support system based on computer vision and parallel computing. Wireless Communications and Mobile Computing, 2022, e7416106. https://doi.org/10.1155/2022/7416106
  • Lopez, A., & Garza, R. (2023). Consumer bias against evaluations received by artificial intelligence: The mediation effect of lack of transparency anxiety. Journal of Research in Interactive Marketing, 17(6), 831–847. https://doi.org/10.1108/JRIM-07-2021-0192
  • Ma, L., & Sun, B. (2020). Machine learning and AI in marketing – Connecting computing power to human insights. International Journal of Research in Marketing, 37(3), 481–504. https://doi.org/10.1016/j.ijresmar.2020.04.005
  • Malodia, S., Islam, N., Kaur, P., & Dhir, A. (2021). Why do people use artificial intelligence (AI)-enabled voice assistants? IEEE Transactions on Engineering Management, 1–15. https://doi.org/10.1109/TEM.2021.3117884
  • Malthouse, E., & Copulsky, J. (2023). Artificial intelligence ecosystems for marketing communications. International Journal of Advertising, 42(1), 128–140. https://doi.org/10.1080/02650487.2022.2122249
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  • Mariciuc, D. F. (2022). Using Virtual Assistants as Relationship Marketing Instruments. Ovidius University Annals, Economic Sciences Series, 22(1), 634–641.
  • Mathew, J., & Scholar, P. G. (2021). A study into the use of artificial intelligence in e-commerce stock management and product suggestion generation for end users. Proceedings of the National Conference on Emerging Computer Applications (NCECA), 103.
  • Mazurek, G., & Małagocka, K. (2019). Perception of privacy and data protection in the context of the development of artificial intelligence. Journal of Management Analytics, 6(4), 344–364. https://doi.org/10.1080/23270012.2019.1671243
  • Mokhtari, S., Yen, K. K., & Liu, J. (2021). Effectiveness of artificial intelligence in stock market prediction based on machine learning. International Journal of Computer Applications, 183(7), 1–8. https://doi.org/10.5120/ijca2021921347
  • Montjoye, Y.-A. de, Farzanehfar, A., Hendrickx, J., & Rocher, L. (2017). Solving artificial intelligence’s privacy problem. Field Actions Science Reports. The Journal of Field Actions, Special Issue 17, Article Special Issue 17.
  • Ngai, E. W. T., & Wu, Y. (2022). Machine learning in marketing: A literature review, conceptual framework and research agenda. Journal of Business Research, 145, 35–48. https://doi.org/10.1016/j.jbusres.2022.02.049
  • Nwachukwu, D., & Affen, M. (2023). Artificial Intelligence Marketing Practices: The Way Forward to Better Customer Experience Management in Africa (Systematic Literature Review). 9, 44–62.
  • Pinarbasi, F., & Akpınar, H. M. (2020). Transformation of marketing with technology: case approach for artificial intelligence. In Handbook of Research on Strategic Fit and Design in Business Ecosystems (pp. 144–165). IGI Global. https://doi.org/10.4018/978-1-7998-1125-1.ch007
  • Prentice, C., Weaven, S., & Wong, I. A. (2020). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629. https://doi.org/10.1016/j.ijhm.2020.102629
  • Rabby, F., & Chimhundu, D. R. (2021). Artificial Intelligence in Digital Marketing Influences Consumer Behaviour: A Review and Theoretical Foundation for Future Research. 25(5).
  • Raiter, O. (2021). Segmentation of bank consumers for artificial intelligence marketing. International Journal of Contemporary Financial Issues, 1(1), 39–54.
  • Ramachandran, K. K., Apsara Saleth Mary, A., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. R. (2022). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings, 51, 2327–2331. https://doi.org/10.1016/j.matpr.2021.11.544
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  • Ray, S. (2019). A quick review of machine learning algorithms. 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon), 35–39. https://doi.org/10.1109/COMITCon.2019.8862451
  • Riikkinen, M., Saarijärvi, H., Sarlin, P., & Lähteenmäki, I. (2018). Using artificial intelligence to create value in insurance. International Journal of Bank Marketing, 36(6), 1145–1168. https://doi.org/10.1108/IJBM-01-2017-0015
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  • Wang, C. (2022). Efficient customer segmentation in digital marketing using deep learning with swarm intelligence approach. Information Processing & Management, 59(6), 103085. https://doi.org/10.1016/j.ipm.2022.103085
  • Wu, C.-W., & Monfort, A. (2023). Role of artificial intelligence in marketing strategies and performance. Psychology & Marketing, 40(3), 484–496. https://doi.org/10.1002/mar.21737
  • Yau, K.-L. A., Saad, N. M., & Chong, Y.-W. (2021). Artificial intelligence marketing (AIM) for enhancing customer relationships. Applied Sciences, 11(18), Article 18. https://doi.org/10.3390/app11188562
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  • Zulaikha, S., Mohamed, H., Kurniawati, M., Rusgianto, S., & Rusmita, S. A. (2020). Customer predictive analytics using artificial intelligence. The Singapore Economic Review, 1–12. https://doi.org/10.1142/S0217590820480021
Toplam 93 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme , Pazarlama (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Hafize Nurgül Durmuş Şenyapar 0000-0003-0927-1643

Erken Görünüm Tarihi 28 Şubat 2024
Yayımlanma Tarihi 29 Şubat 2024
Gönderilme Tarihi 30 Aralık 2023
Kabul Tarihi 18 Şubat 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 8 Sayı: 15

Kaynak Göster

APA Durmuş Şenyapar, H. N. (2024). The Future of Marketing: The Transformative Power of Artificial Intelligence. International Journal of Management and Administration, 8(15), 1-19. https://doi.org/10.29064/ijma.1412272