UNDERSTANDING AI-DRIVEN INFLUENCER MARKETING
DOI:
https://doi.org/10.54443/injoss.v2i3.90Keywords:
AI-driven, Influencer marketing, Efficiency, Effectiveness, Campaign performance, Ethical considerations, Algorithmic biases, prospects.Abstract
AI-driven influencer marketing has emerged as a transformative approach in the digital advertising landscape. This research aimed to explore the efficiency and effectiveness of AI integration in influencer marketing campaigns, comparing it to traditional methods. By employing a mixed-methods approach, including qualitative interviews and quantitative data analysis, the study investigated the impact of AI on influencer selection, campaign performance, and ethical considerations. The findings revealed that AI-driven influencer selection processes significantly outperformed manual methods' accuracy and efficiency. AI algorithms effectively matched influencers with target audiences, increasing engagement rates and brand visibility. The real-time analytics provided by AI tools enabled marketers to make data-driven decisions and optimize campaign strategies on-the-fly. Moreover, AI-optimized influencer campaigns consistently surpassed traditional campaigns in metrics such as reach, impressions, and ROI. The data-backed approach of AI led to more targeted and relevant campaigns, resonating better with the audience and yielding tangible results for businesses. However, ethical considerations regarding algorithmic biases were identified as crucial aspects of AI-driven influencer marketing. Transparent practices and ongoing audits of AI algorithms were emphasized to mitigate biases and ensure ethical influencer selections. Looking ahead, the future of AI for influencer marketing appears promising. Advancements in AI algorithms will lead to even more accurate influencer matches and sophisticated audience insights, fostering hyper-personalized campaigns. By embracing AI technologies responsibly, businesses can connect with their target audiences more effectively and stay ahead in the dynamic realm of digital advertising.
References
Balaban, D., & Mustățea, M. (2019). Users’ perspective on the credibility of social media influencers in Romania and Germany. Romanian Journal of Communication and Public Relations, 21(1), 31-46.
Bognar, Z. B., Puljic, N. P., & Kadezabek, D. (2019). Impact of influencer marketing on consumer behaviour. Economic and Social Development: Book of Proceedings, 301-309.
Böhndel, M., Jastorff, M., & Rudeloff, C. (2023). AI-driven influencer marketing: Comparing the effects of virtual and human influencers on consumer perceptions. Journal of AI, Robotics & Workplace Automation, 2(2), 165-174.
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.
Chadha, U., Selvaraj, S. K., Raj, A., Mahanth, T., Vignesh, S. P., Lakshmi, P. J., ... & Adefris, A. (2022). AI-driven techniques for controlling the metal melting production: a review, processes, enabling technologies, solutions, and research challenges. Materials Research Express, 9(7), 072001.
Chaffey, D., & Smith, P. R. (2022). Digital marketing excellence: planning, optimizing and integrating online marketing. Taylor & Francis.
Chaffey, D., & Smith, P. R. (2022). Digital marketing excellence: planning, optimizing and integrating online marketing. Taylor & Francis.
Chaitanya, K., Saha, G. C., Saha, H., Acharya, S., & Singla, M. (2023). The Impact of Artificial Intelligence and Machine Learning in Digital Marketing Strategies. European Economic Letters (EEL), 13(3), 982-992.
Chaitanya, K., Saha, G. C., Saha, H., Acharya, S., & Singla, M. (2023). The Impact of Artificial Intelligence and Machine Learning in Digital Marketing Strategies. European Economic Letters (EEL), 13(3), 982-992.
Childers, C. C., Lemon, L. L., & Hoy, M. G. (2019). # Sponsored# Ad: Agency perspective on influencer marketing campaigns. Journal of Current Issues & Research in Advertising, 40(3), 258-274.
Dostatni, E., Mikołajewski, D., Dorożyński, J., & Rojek, I. (2022). Ecological Design with the Use of Selected Inventive Methods including AI-Based. Applied Sciences, 12(19), 9577.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., ... & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168.
Feng, Y., Chen, H., & Kong, Q. (2021). An expert with whom I can identify: The role of narratives in influencer marketing. International Journal of Advertising, 40(7), 972-993.
Fianto, A. Y. A. (2023). Artificial Intelligence and Novel Services: Exploring Opportunities in the Marketing Landscape. Journal of Applied Management and Business, 4(1), 49-59.
Floridi, L., Cowls, J., King, T. C., & Taddeo, M. (2021). How to design AI for social good: seven essential factors. Ethics, Governance, and Policies in Artificial Intelligence, 125-151.
Galletta, A. (2013). Mastering the semi-structured interview and beyond: From research design to analysis and publication (Vol. 18). NYU press.
Gupta, S., Justy, T., Kamboj, S., Kumar, A., & Kristoffersen, E. (2021). Big data and firm marketing performance: Findings from knowledge-based view. Technological Forecasting and Social Change, 171, 120986.
Haenlein, M., Anadol, E., Farnsworth, T., Hugo, H., Hunichen, J., & Welte, D. (2020). Navigating the New Era of Influencer Marketing: How to be Successful on Instagram, TikTok, & Co. California management review, 63(1), 5-25.
Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks.
He, A. Z., & Zhang, Y. (2023). AI-powered touch points in the customer journey: a systematic literature review and research agenda. Journal of Research in Interactive Marketing, 17(4), 620-639.
Hudders, L., & Lou, C. (2023). The rosy world of influencer marketing? Its bright and dark sides, and future research recommendations. International Journal of Advertising, 42(1), 151-161.
Johnson, J. L., Adkins, D., & Chauvin, S. (2020). A review of the quality indicators of rigor in qualitative research. American journal of pharmaceutical education, 84(1).
Kim, J. (2020). The influence of perceived costs and perceived benefits on AI-driven interactive recommendation agent value. Journal of Global Scholars of Marketing Science, 30(3), 319-333.
Le, K., & Aydin, G. (2022). Impact of the pandemic on social media influencer marketing in fashion: a qualitative study. Qualitative Market Research: An International Journal.
Lee, D., & Ham, C. D. (2023). AI versus Human: Rethinking the Role of Agent Knowledge in Consumers’ Coping Mechanism Related to Influencer Marketing. Journal of Interactive Advertising, 1-18.
Lee, D., & Ham, C. D. (2023). AI versus Human: Rethinking the Role of Agent Knowledge in Consumers’ Coping Mechanism Related to Influencer Marketing. Journal of Interactive Advertising, 1-18.
Leung, F. F., Gu, F. F., & Palmatier, R. W. (2022). Online influencer marketing. Journal of the Academy of Marketing Science, 1-26.
Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of interactive advertising, 19(1), 58-73.
Mouritzen, S. L. T., Penttinen, V., & Pedersen, S. (2023). Virtual influencer marketing: the good, the bad and the unreal. European Journal of Marketing.
Tanwar, A. S., Chaudhry, H., & Srivastava, M. K. (2022). Trends in influencer marketing: a review and bibliometric analysis. Journal of Interactive Advertising, 22(1), 1-27.
Taylor, C. R. (2020). The urgent need for more research on influencer marketing. International Journal of Advertising, 39(7), 889-891.
Varadarajan, R., Welden, R. B., Arunachalam, S., Haenlein, M., & Gupta, S. (2022). Digital product innovations for the greater good and digital marketing innovations in communications and channels: Evolution, emerging issues, and future research directions. International Journal of Research in Marketing, 39(2), 482-501.
Wamba-Taguimdje, S. L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893-1924.
Wamba-Taguimdje, S. L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893-1924.
Wandl, A. (2020). Research Design and Approach. A+ BE| Architecture and the Built Environment, (02), 37-78.
Ye, G., Hudders, L., De Jans, S., & De Veirman, M. (2021). The value of influencer marketing for business: A bibliometric analysis and managerial implications. Journal of Advertising, 50(2), 160-178.
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