ARTIFICIAL INTELLIGENCE (AI) OPTIMALIZATION IN CUSTOMER BEHAVIOR ANALYSIS TO DETERMINE MARKETING STRATEGIES: SYSTEMATIC LITERATURE REVIEW
Downloads
Objective: This research aims to examine the optimization of the use of AI in understanding and analyzing customer behavior in developing effective and efficient marketing strategies. Method: The method used in this research is the SLR (Systematic Literature Review) method, by collecting data through various sources of academic database articles such as Google Scholar, IEEE Xplore, Science Direct and others that discuss the application of AI. Results: The results of this literature review show that the application of AI such as machine learning and data analysis is able to identify customer preferences and needs, which will be used by companies in designing more personalized and efficient marketing strategies. Novelty: In the digital era, the use of artificial intelligence (AI) in customer behavior analysis has become one of the effective tools to determine a more appropriate marketing strategy. Optimizing AI through the SLR method is an important step for companies in achieving a competitive advantage in understanding customer behavior patterns more accurately in a dynamic market.
E. Y. Pratiwi, A. Z. Haq, and Z. D. Daufa, “AI DALAM MANAJEMEN RISIKO UNTUK MEMBANGUN KEPUTUSAN KEUANGAN YANG LEBIH BAIK : SYSTEMATIC LITERATURE REVIEW,” vol. 9, no. 1, pp. 999–1004, 2025.
P. Rita, T. Oliveira, and A. Farisa, “The impact of e-service quality and customer satisfaction on customer behavior in online shopping,” Heliyon, vol. 5, no. 10, p. e02690, 2019.
Rini Wijayaningsih et al., “Pemanfaatan Kecerdasan Buatan dalam Transformasi Intelejen Bisnis untuk Keunggulan Kompetitif,” CEMERLANG J. Manaj. dan Ekon. Bisnis, vol. 4, no. 3, pp. 136–141, 2024.
Aditya Nirwana, Sudarmiatin, and Melany, “Implementation of Artificial Intelligence in Digital Marketing Development: a Thematic Review and Practical Exploration,” J. Manaj. Bisnis, Akunt. dan Keuang., vol. 2, no. 1, pp. 85–112, 2023.
S. Faradillah, D. Irmansyah, B. A. Lokatara, M. I. Saputra, and A. Wulansari, “Analisis Perkembangan Artificial Intelligence Dalam Bidang Bisnis : Systematic Literature Review,” Djtechno J. Teknol. Inf., vol. 4, no. 2, pp. 298–309, 2023.
A. Dinata and M. I. P. Nasution, “PENERAPAN AI DALAM SISTEM INFORMASI MANAJEMEN UNTUK MENINGKATKAN EFISIENSI BISNIS (APPLICATION OF AI IN MANAGEMENT INFORMATION SYSTEM TO IMPROVE BUSINESS EFFICIENCY),” J. Rumpun Manaj. dan Ekon., vol. 2, no. 1, pp. 156–161, 2025.
P. Konsumen and D. I. Bisnis, “EFEKTIVITAS PENGGUNAAN ARTIFICIAL INTELLIGENCE DALAM ANALISIS,” no. November, pp. 156–160, 2024.
F. Fidiyanti, A. Rifky Subagja, R. Pridharma Wachyu, and H. Madiistriyatno, “Analisis Strategi Pengembangan Bisnis Menggunakan Teknologi Artificial Intelegence,” J. Compr. Sci., vol. 2, no. 7, pp. 1994–2001, 2023.
E. Triandini, S. Jayanatha, A. Indrawan, G. Werla Putra, and B. Iswara, “Metode Systematic Literature Review untuk Identifikasi Platform dan Metode Pengembangan Sistem Informasi di Indonesia,” Indones. J. Inf. Syst., vol. 1, no. 2, p. 63, 2019.
dan S. S. Yansen Makleat, Fauzia Ramadhan, Abdul Cholis, “Systematic Literatur Review ( SLR ): Metode , Manfaat , Dan Tantangan Learning Analytics Dengan Metode Data Mining di Dunia Pendidikan Tinggi,” J. Ilm. INFOKAM, vol. 13, no. 1, pp. 73–86, 2017.
D. C. Gkikas and P. K. Theodoridis, “AI in consumer behavior,” Adv. Artif. Intell. Technol. Sel. Pap. Honour Profr. Nikolaos G. Bourbakis—Vol. 1, pp. 147–176, 2022.
E. S. Pemasaran, “1 , 2 1,2,” vol. 5, no. 8, pp. 1–11, 2024.
D. F. Rizaldi, J. Abdillah, M. Naufal, M. A. Yaqin, and A. C. Fauzan, “Survei Pengukuran Fleksibilitas Software Menggunakan Metode Systematic Literature Review,” Ilk. J. Comput. Sci. Appl. Informatics, vol. 4, no. 1, pp. 53–66, 2022.
A. D. Ekawati, S. K. Ningsih, Y. Suwartini, and E. C. Wenno, “Penulisan Systematic Literature Review (Slr) Pada Jurnal Terindeks,” Abdi Dosen J. Pengabdi. Pada Masy., vol. 5, no. 4, p. 645, 2021.
C. G. Thomas and C. G. Thomas, “Academic Databases,” 2021, Springer.
E. S. Eriana and A. Zein, “Artificial Intelligence (AI),” 2023.
A. A. Khade, “Performing customer behavior analysis using big data analytics,” Procedia Comput. Sci., vol. 79, pp. 986–992, 2016.
N. A. Morgan, K. A. Whitler, H. Feng, and S. Chari, “Research in marketing strategy,” J. Acad. Mark. Sci., vol. 47, pp. 4–29, 2019.
M. I. Jordan and T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science (80-. )., vol. 349, no. 6245, pp. 255–260, 2015.
K. Porritt, J. Gomersall, and C. Lockwood, “JBI’s systematic reviews: study selection and critical appraisal,” AJN Am. J. Nurs., vol. 114, no. 6, pp. 47–52, 2014.
T. Mathes, P. Klaßen, and D. Pieper, “Frequency of data extraction errors and methods to increase data extraction quality: a methodological review,” BMC Med. Res. Methodol., vol. 17, pp. 1–8, 2017.
L. Harvey and J. Newton, “Transforming quality evaluation,” Qual. High. Educ., vol. 10, no. 2, pp. 149–165, 2004.
M. Stuiver and H. A. Polach, “Discussion reporting of 14C data,” Radiocarbon, vol. 19, no. 3, pp. 355–363, 1977.
C.-K. Huang, T.-Y. Chang, and B. G. Narayanan, “Mining the change of customer behavior in dynamic markets,” Inf. Technol. Manag., vol. 16, pp. 117–138, 2015.
N. Gautam and N. Kumar, “Customer segmentation using k-means clustering for developing sustainable marketing strategies,” Бизнес-информатика, vol. 16, no. 1 (eng), pp. 72–82, 2022.
A. Smith and J. Anderson, “AI, Robotics, and the Future of Jobs,” Pew Res. Cent., vol. 6, 2014.
G. Chmielarz, “3 Data Entrepreneurial Privacy and Responsibility,” Digit. Sustain. Navig. Entrep. Inf. Age, p. 36, 2024.
P. Menard and G. J. Bott, “Artificial intelligence misuse and concern for information privacy: New construct validation and future directions,” Inf. Syst. J., 2024.
N. Ojha and V. P. Nikhil, “Challenges of AI Implementation for Boosting Circular Economy in Smart Cities,” in Smart Cities and Circular Economy, Emerald Publishing Limited, 2024, pp. 215–233.
D. S. Wishart et al., “HMDB 5.0: the human metabolome database for 2022,” Nucleic Acids Res., vol. 50, no. D1, pp. D622–D631, 2022.
X. Wang, “Accurate marketing strategies based on data analytics,” in Journal of Physics: Conference Series, IOP Publishing, 2021, p. 42201.
L.-W. Wang, C.-C. Hung, and C.-T. Hsieh, “[Retracted] Enterprise Precision Marketing Strategy and Quality Management Mobile Information System Based on Customer Satisfaction,” Mob. Inf. Syst., vol. 2022, no. 1, p. 2105383, 2022.
M. Stone et al., “Artificial intelligence (AI) in strategic marketing decision-making: a research agenda,” Bottom Line, vol. 33, no. 2, pp. 183–200, 2020.
D. Kalaivani and P. Sumathi, “Factor based prediction model for customer behavior analysis,” Int. J. Syst. Assur. Eng. Manag., vol. 10, no. 4, pp. 519–524, 2019.
C. Ledro, A. Nosella, and I. Dalla Pozza, “Integration of AI in CRM: Challenges and guidelines,” J. Open Innov. Technol. Mark. Complex., vol. 9, no. 4, p. 100151, 2023.
Z. You, Y.-W. Si, D. Zhang, X. Zeng, S. C. H. Leung, and T. Li, “A decision-making framework for precision marketing,” Expert Syst. Appl., vol. 42, no. 7, pp. 3357–3367, 2015.
Copyright (c) 2025 Amanda Tiara Prameswari, Alshaf Pebrianggara, Mochamad Rizal Yulianto, Istian Kriya Almanfaluti

This work is licensed under a Creative Commons Attribution 4.0 International License.



