REVOLUTIONIZING SOCIAL MEDIA MARKETING THROUGH AI AND AUTOMATION: AN IN-DEPTH ANALYSIS OF STRATEGIES, ETHICS, AND FUTURE TRENDS

Authors

  • Doby Indrawan Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia
  • Yorman Yorman Universitas Nahdlatul Wathan Mataram, Indonesia
  • Muhamad Stiadi Universitas Sembilanbelas November Kolaka, Indonesia
  • Nenden Hendayani Universitas Sali Alaitam, Indonesia
  • Al- Amin Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi, Indonesia

Keywords:

Revolutionizing, Social Media Marketing, Artificial Intelligence (AI), Automation, Strategies, Ethics, Future Trends, Data-driven Decision-making.

Abstract

This comprehensive analysis delved into the transformative potential of artificial intelligence (AI) and automation in social media marketing. We explored many strategies and insights that have redefined how businesses engage with their audiences in the digital age. Our investigation began by acknowledging the profound impact of AI and automation technologies on the marketing landscape, particularly within the dynamic domain of social media. These innovations ushered in a new era of data-driven decision-making, hyper-personalization, and efficiency, enabling marketers to create more targeted and impactful campaigns. A key finding of our analysis was the pivotal role of AI in audience segmentation and targeting. Through real-time data analysis, marketers could identify and engage their ideal audience segments with exceptional precision, optimizing resource allocation and campaign effectiveness. We also highlighted the emergence of AI-driven chatbots and virtual assistants, revolutionizing customer service and engagement on social media platforms. These 24/7 available, personalized interaction tools significantly enhanced the overall customer experience. However, amidst the transformative potential of AI and automation, we emphasized the ethical responsibilities accompanying these advancements. We stressed the need for transparency, data privacy, and fairness in AI-driven marketing practices. Upholding these principles ensures trust, a cornerstone of long-term success. In conclusion, our analysis illuminated the remarkable potential of AI and automation in revolutionizing social media marketing. As we move forward into this era of technological transformation, we must do so with a steadfast commitment to innovation and ethical integrity, shaping a marketing landscape that benefits businesses and consumers alike.

References

Abdulquadri, A., Mogaji, E., Kieu, T. A., & Nguyen, N. P. (2021). Digital transformation in financial services provision: A Nigerian perspective to adopting chatbot. Journal of Enterprising Communities: People and Places in the Global Economy, 15(2), 258-281.

Aiolfi, S., Bellini, S., & Pellegrini, D. (2021). Data-driven digital advertising: benefits and risks of online behavioral advertising. International Journal of Retail & Distribution Management, 49(7), 1089-1110.

Andrus, M., & Villeneuve, S. (2022, June). Demographic-reliant algorithmic fairness: Characterizing the risks of demographic data collection in the pursuit of fairness. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 1709-1721).

Bala, M., & Verma, D. (2018). A critical review of digital marketing. M. Bala, D. Verma (2018). A Critical Review of Digital Marketing. International Journal of Management, IT & Engineering, 8(10), 321–339.

Barker, C., Pistrang, N., & Elliott, R. (2015). Research methods in clinical psychology: An introduction for students and practitioners. John Wiley & Sons.

Bredfell, A., & Roll, G. (2023). Predicting Cross-Platform Performance: A Case Study on Evaluating Predictive Models and Exploring the Economic Consequences in Software Testing.

Brown, R. (Ed.). (2018). Knowledge, education, and cultural change: papers in the sociology of education (Vol. 3). Routledge.

Bryson, J. J. (2020). The artificial intelligence of the ethics of artificial intelligence. The Oxford Handbook of Ethics of AI, 1.

Campbell, C., Sands, S., Ferraro, C., Tsao, H. Y. J., & Mavrommatis, A. (2020). From data to action: How marketers can leverage AI. Business Horizons, 63(2), 227–243.

Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications, 10(1), 1–12.

Choi, M. (2016). A concept analysis of digital citizenship for democratic citizenship education in the Internet age. Theory & research in social education, 44(4), 565–607.

Clarke, R. (2019). Principles and business processes for responsible AI. Computer Law & Security Review, 35(4), 410–422.

Connelly, L. M. (2014). Ethical considerations in research studies. Medsurg nursing, 23(1), 54–56.

De La Garza, L. A., Farrow, A., Lam, R., & Shum, L. (2022). A Scenario for the Future of AI and Technology in Public Education. The journal: Student Journal of the University of Toronto's Faculty of Information, 8(1).

Emanuel, E. J., Persad, G., Upshur, R., Thome, B., Parker, M., Glickman, A., ... & Phillips, J. P. (2020). Fair allocation of scarce medical resources in the time of Covid-19. New England Journal of Medicine, 382(21), 2049-2055.

Garrido, A., M’Barek, R., Bardají, I., Meuwissen, M. P., Morales-Opazo, C., & Viñas, J. M. S. (2016). Scope and objectives. In Agricultural Markets Instability (pp. 1-12). Routledge.

Girasa, R. (2020). Artificial intelligence as a disruptive technology: Economic transformation and government regulation. Springer Nature.

Gonçalves, A. R., Pinto, D. C., Rita, P., & Pires, T. (2023). Artificial Intelligence and Its Ethical Implications for Marketing. Emerging Science Journal, 7(2), 313-327.

Górriz, J. M., Ramírez, J., Ortíz, A., Martinez-Murcia, F. J., Segovia, F., Suckling, J., ... & Ferrandez, J. M. (2020). Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends, and applications. Neurocomputing, 410, 237-270.

Gupta, A., Anpalagan, A., Guan, L., & Khwaja, A. S. (2021). Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues. Array, 10, 100057.

Hacioglu, U. (Ed.). (2019). Digital business strategies in blockchain ecosystems: Transformational design and future of global business. Springer Nature.

Isabelle, D., Westerlund, M., Mane, M., & Leminen, S. (2020). The role of analytics in data-driven business models of multi-sided platforms: An exploration in the food industry.

Jin, B. E., & Shin, D. C. (2021). The power of the Fourth Industrial Revolution in the fashion industry: What, why, and How has the industry changed? Fashion and Textiles, 8(1), 1–25.

Kamal, M., & Himel, A. S. (2023). Redefining Modern Marketing: A Comprehensive Analysis of AI and NLP's Influence on Consumer Engagement, Strategy, and Beyond. Eigenpub Review of Science and Technology, 7(1), 202-223.

Klimeš, D. (2021). Conceptualizing" Sponsored Authenticity" in Sustainable Influencer Marketing. Marketing Identity, 9(1), 314–324.

Kushwaha, A. K., Kumar, P., & Kar, A. K. (2021). What impacts customer experience for B2B enterprises on using AI-enabled chatbots? Insights from Big data analytics. Industrial Marketing Management, pp. 98, 207–221.

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.

McGowan, J., Sampson, M., Salzwedel, D. M., Cogo, E., Foerster, V., & Lefebvre, C. (2016). PRESS peer review of electronic search strategies: 2015 guideline statement. Journal of Clinical Epidemiology, 75, 40-46.

Munn, Z., Tufanaru, C., & Aromataris, E. (2014). JBI's systematic reviews: data extraction and synthesis. AJN The American Journal of Nursing, 114(7), 49-54.

Murgai, A. (2018). Transforming digital marketing with artificial intelligence. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(4), 259–262.

Prasad Agrawal, K. (2023). Towards adoption of Generative AI in organizational settings. Journal of Computer Information Systems, 1-16.

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of business research, 104, 333-339.

Evans, L., Rhodes, A., Alhazzani, W., Antonelli, M., Coopersmith, C. M., French, C., ... & Levy, M. (2021). Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Critical care medicine, 49(11), e1063-e1143.

Pati, D., & Lorusso, L. N. (2018). How to write a systematic review of the literature. HERD: Health Environments Research & Design Journal, 11(1), 15-30.

Miller, D. (Ed.). (2021). Home possessions: material culture behind closed doors. Routledge.

Peyravi, B., Nekrošienė, J., & Lobanova, L. (2020). Revolutionized technologies for marketing: Theoretical review with a focus on artificial intelligence. Business: Theory and Practice, 21(2), 827-834.

Rathore, B. (2017). Beyond Trends: Shaping the Future of Fashion Marketing with AI, Sustainability and Machine Learning. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 6(2), 16–24.

Ridder, H. G. (2017). The theory contribution of case study research designs. Business research, 10, 281-305.

Rivas, P., & Zhao, L. (2023). Marketing with chatbot: Navigating the ethical terrain of gpt-based chatbot technology. AI, 4(2), 375-384.

Sadiku, M. N., Ashaolu, T. J., Ajayi-Majebi, A., & Musa, S. M. (2021). Artificial intelligence in social media. International Journal of Scientific Advances, 2(1), 15-20.

Santiago, J. K., & Castelo, I. M. (2020). Digital influencers: An exploratory study of influencer marketing campaign process on Instagram. Online Journal of Applied Knowledge Management (OJAKM), 8(2), 31-52.

Shin, D. (2020). User perceptions of algorithmic decisions in the personalized AI system: Perceptual evaluation of fairness, accountability, transparency, and explainability. Journal of Broadcasting & Electronic Media, 64(4), 541–565.

Soliman, M., & Al Balushi, M. K. (2023). Unveiling destination evangelism through generative AI tools. ROBONOMICS: The Journal of the Automated Economy, 4(54), 1.

Stamatakis, G., Kontaxakis, A., Simitsis, A., Giatrakos, N., & Deligiannakis, A. (2022). SheerMP: Optimized Streaming Analytics-as-a-Service over Multi-site and Multi-platform Settings. In EDBT (pp. 2-558).

Tarek, A. (2023). Intellectual Property Implications of Artificial Intelligence and Ownership of AI-Generated Works. Available at SSRN 4494640.

Thakker, P., & Japee, G. (2023). Emerging Technologies in Accountancy and Finance: A Comprehensive Review. European Economic Letters (EEL), 13(3), 993-1011.

Thieme, A., Hanratty, M., Lyons, M., Palacios, J., Marques, R. F., Morrison, C., & Doherty, G. (2023). Designing human-centered AI for mental health: Developing clinically relevant applications for online CBT treatment. ACM Transactions on Computer-Human Interaction, 30(2), 1–50.

Tsinaslanidis, S. (2023). Marketing mix modeling algorithms for the FMCG industry.

Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.

Wachter, S., Mittelstadt, B., & Floridi, L. (2017). Why a right to an explanation of automated decision-making does not exist in the general data protection regulation. International Data Privacy Law, 7(2), 76-99.

Wang, Y. (2023). Synthetic Realities in the Digital Age: Navigating the Opportunities and Challenges of AI-Generated Content.

Wellman, M. L., Stoldt, R., Tully, M., & Ekdale, B. (2020). Ethics of authenticity: Social media influencers and the production of sponsored content. Journal of Media Ethics, 35(2), 68–82.

Wierenga, B. (2021). The study of essential marketing issues in an evolving field. International Journal of Research in Marketing, 38(1), 18–28.

Zhang, J. Z., & Watson IV, G. F. (2020). Marketing Ecosystem: An outside-in view for sustainable advantage. Industrial Marketing Management, pp. 88, 287–304.

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Published

2023-09-30

How to Cite

Indrawan, D., Yorman, Y., Stiadi, M. ., Hendayani, N. ., & Amin, A.-. (2023). REVOLUTIONIZING SOCIAL MEDIA MARKETING THROUGH AI AND AUTOMATION: AN IN-DEPTH ANALYSIS OF STRATEGIES, ETHICS, AND FUTURE TRENDS. International Journal Of Humanities, Social Sciences And Business (INJOSS), 3(1), 22–45. Retrieved from https://www.injoss.org/index.php/joss/article/view/107

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