Consumer Behavior in the Age of AI: The Role of Personalized Marketing and Data Analytics in Shaping Purchase Decisions
DOI:
https://doi.org/10.38035/dijemss.v5i6.2947Keywords:
Personalized Marketing, Data Analytics, Consumer BehaviorAbstract
In the contemporary digital era, artificial intelligence (AI) has revolutionized the landscape of consumer behavior by enabling personalized marketing and advanced data analytics. This article reviews existing literature to explore the role of AI in shaping purchase decisions. The emergence of AI technologies allows marketers to leverage vast amounts of consumer data to create personalized experiences, enhancing customer engagement and satisfaction. Through personalized marketing strategies, companies can deliver tailored content, product recommendations, and targeted advertisements that align with individual consumer preferences. The integration of data analytics provides deeper insights into consumer behavior, enabling businesses to anticipate trends and make informed decisions. This literature review examines various case studies and empirical research to highlight the effectiveness of AI-driven marketing strategies in influencing consumer purchase decisions. The findings indicate that personalized marketing, underpinned by sophisticated data analytics, not only enhances consumer trust and loyalty but also drives higher conversion rates. This study underscores the importance of embracing AI technologies for businesses aiming to stay competitive in an increasingly digital marketplace.
References
Al Naqbi, H., Bahroun, Z., & Ahmed, V. (2024). Enhancing work productivity through generative artificial intelligence: A comprehensive literature review. Sustainability, 16(3), 1166. https://doi.org/10.3390/su16031166
Alawadh, M., & Barnawi, A. (2024). A consumer behavior analysis framework toward improving market performance indicators: Saudi’s retail sector as a case study. Journal of Theoretical and Applied Electronic Commerce Research, 19(1), 152-171. https://doi.org/10.3390/jtaer19010009
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2024). AI-powered innovation in digital transformation: Key pillars and industry impact. Sustainability, 16(5), 1790. https://doi.org/10.3390/su16051790
Alhumud, A. A., & Elshaer, I. A. (2024). Social commerce and customer-to-customer value co-creation impact on sustainable customer relationships. Sustainability, 16(10), 4237. https://doi.org/10.3390/su16104237
Alhumud, A. A., & Elshaer, I. A. (2024). Social commerce and customer-to-customer value co-creation impact on sustainable customer relationships. Sustainability, 16(10), 4237. https://doi.org/10.3390/su16104237
Ali, S. E. A., Lai, F.-W., Hassan, R., & Shad, M. K. (2021). The long-run impact of information security breach announcements on investors’ confidence: The context of efficient market hypothesis. Sustainability, 13(3), 1066. https://doi.org/10.3390/su13031066
Alojail, M., & Khan, S. B. (2023). Impact of Digital Transformation toward Sustainable Development. Sustainability, 15(20), 14697. https://doi.org/10.3390/su152014697
Anas, A. M., Abdou, A. H., Hassan, T. H., Alrefae, W. M. M., Daradkeh, F. M., El-Amin, M. A.-M., ... Alboray, H. M. M. (2023). Satisfaction on the Driving Seat: Exploring the Influence of Social Media Marketing Activities on Followers’ Purchase Intention in the Restaurant Industry Context. Sustainability, 15(9), 7207. https://doi.org/10.3390/su15097207
Bianchini, A., Savini, I., Andreoni, A., Morolli, M., & Solfrini, V. (2024). Manufacturing Execution System Application within Manufacturing Small–Medium Enterprises towards Key Performance Indicators Development and Their Implementation in the Production Line. Sustainability, 16(7), 2974. https://doi.org/10.3390/su16072974
Brambilla, M., Badrizadeh, H., Malek Mohammadi, N., & Javadian Sabet, A. (2023). Analyzing brand awareness strategies on social media in the luxury market: The case of Italian fashion on Instagram. Digital, 3(1), 1-17. https://doi.org/10.3390/digital3010001
Chae, M.-J. (2021). Driving consumer engagement through diverse calls to action in corporate social responsibility messages on social media. Sustainability, 13(7), 3812. https://doi.org/10.3390/su13073812
Chong, W. K., & Patwa, N. (2023). The value of integrity: Empowering SMEs with ethical marketing communication. Sustainability, 15(15), 11673. https://doi.org/10.3390/su151511673
Garanti, Z., Ilkhanizadeh, S., & Liasidou, S. (2024). Sustainable place branding and visitors’ responses: A systematic literature review. Sustainability, 16(8), 3312. https://doi.org/10.3390/su16083312
Goedertier, F., Weijters, B., & Van den Bergh, J. (2024). Are Consumers Equally Willing to Pay More for Brands That Aim for Sustainability, Positive Societal Contribution, and Inclusivity as for Brands That Are Perceived as Exclusive? Generational, Gender, and Country Differences. Sustainability, 16(9), 3879. https://doi.org/10.3390/su16093879
Guo, J., Zhang, W., & Xia, T. (2023). Impact of shopping website design on customer satisfaction and loyalty: The mediating role of usability and the moderating role of trust. Sustainability, 15(8), 6347. https://doi.org/10.3390/su15086347
Hemker, S., Herrando, C., & Constantinides, E. (2021). The transformation of data marketing: How an ethical lens on consumer data collection shapes the future of marketing. Sustainability, 13(20), 11208. https://doi.org/10.3390/su132011208
Huynh, H., Wojdyla, W., Van Dyk, C., Yang, Z., & Chi, T. (2024). Transparent threads: Understanding how U.S. consumers respond to traceable information in fashion. Sustainability, 16(12), 5010. https://doi.org/10.3390/su16125010
Jiang, Y., Rezazadeh Baee, M. A., Simpson, L. R., Gauravaram, P., Pieprzyk, J., Zia, T., ... Le, Z. (2024). Pervasive user data collection from cyberspace: Privacy concerns and countermeasures. Cryptography, 8(1), 5. https://doi.org/10.3390/cryptography8010005
Jung, S.-U., & Shegai, V. (2023). The Impact of Digital Marketing Innovation on Firm Performance: Mediation by Marketing Capability and Moderation by Firm Size. Sustainability, 15(7), 5711. https://doi.org/10.3390/su15075711
Licardo, J. T., Domjan, M., & Orehova?ki, T. (2024). Intelligent robotics—A systematic review of emerging technologies and trends. Electronics, 13(3), 542. https://doi.org/10.3390/electronics13030542
Lin, R.-H., Chuang, W.-W., Chuang, C.-L., & Chang, W.-S. (2021). Applied big data analysis to build customer product recommendation model. Sustainability, 13(9), 4985. https://doi.org/10.3390/su13094985
Liu, C., & Xu, Y. (2021). Consumer Sentiment Involvement in Big Data Analytics and Its Impact on Product Design Innovation. Sustainability, 13(21), 11821. https://doi.org/10.3390/su132111821
Moreno-Armendáriz, M. A., Calvo, H., Faustinos, J., & Duchanoy, C. A. (2023). Personalized Advertising Design Based on Automatic Analysis of an Individual’s Appearance. Applied Sciences, 13(17), 9765. https://doi.org/10.3390/app13179765
Moreno-Armendáriz, M. A., Calvo, H., Faustinos, J., & Duchanoy, C. A. (2023). Personalized advertising design based on automatic analysis of an individual’s appearance. Applied Sciences, 13(17), 9765. https://doi.org/10.3390/app13179765
Mylrea, M., & Robinson, N. (2023). Artificial Intelligence (AI) trust framework and maturity model: Applying an entropy lens to improve security, privacy, and ethical AI. Entropy, 25(10), 1429. https://doi.org/10.3390/e25101429
Nogueira, M., Silva, B., & Gomes, S. (2023). The impact of customer-centric sustainability on brand relationships. Sustainability, 15(16), 12212. https://doi.org/10.3390/su151612212
Pereira, I., Madureira, A., Bettencourt, N., Coelho, D., Rebelo, M. Â., Araújo, C., & de Oliveira, D. A. (2024). A machine learning as a service (MLaaS) approach to improve marketing success. Informatics, 11(2), 19. https://doi.org/10.3390/informatics11020019
Pressman, S. M., Borna, S., Gomez-Cabello, C. A., Haider, S. A., Haider, C., & Forte, A. J. (2024). AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research. Healthcare, 12(8), 825. https://doi.org/10.3390/healthcare12080825
Schlosky, M. T. T., Karadas, S., & Raskie, S. (2024). ChatGPT, help! I am in financial trouble. Journal of Risk and Financial Management, 17(6), 241. https://doi.org/10.3390/jrfm17060241
Stalidis, G., Karaveli, I., Diamantaras, K., Delianidi, M., Christantonis, K., Tektonidis, D., ... Salampasis, M. (2023). Recommendation Systems for e-Shopping: Review of Techniques for Retail and Sustainable Marketing. Sustainability, 15(23), 16151. https://doi.org/10.3390/su152316151
Tao, S., Liu, S., Zhou, H., & Mao, X. (2024). Research on inventory sustainable development strategy for maximizing cost-effectiveness in supply chain. Sustainability, 16(11), 4442. https://doi.org/10.3390/su16114442
Teodorescu, D., Aivaz, K.-A., Vancea, D. P. C., Condrea, E., Dragan, C., & Olteanu, A. C. (2023). Consumer Trust in AI Algorithms Used in E-Commerce: A Case Study of College Students at a Romanian Public University. Sustainability, 15(15), 11925. https://doi.org/10.3390/su151511925
Uribe-Linares, G. P., Ríos-Lama, C. A., & Vargas-Merino, J. A. (2023). Is There an Impact of Digital Transformation on Consumer Behaviour? An Empirical Study in the Financial Sector. Economies, 11(5), 132. https://doi.org/10.3390/economies11050132
Wang, M., Marsden, J., Oguz, E., & Thomas, B. (2023). Exploring Sustainable Retail Experiences: Shall We Make It Fashionable? Sustainability, 15(23), 16478. https://doi.org/10.3390/su152316478
Wibowo, A., Chen, S.-C., Wiangin, U., Ma, Y., & Ruangkanjanases, A. (2021). Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience. Sustainability, 13(1), 189. https://doi.org/10.3390/su13010189
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
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Copyright (c) 2024 Izharuddin Pagala, Muhammad Asir, Klemens Mere, Utami Puji Lestari, Heidi Siddiqa

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