Business and social sciences | Online ISSN 3067-8919
RESEARCH ARTICLE   (Open Access)

AI's Exceptional Potential to Significantly Improve the Profitability of Social Media Influencer Marketing

Md Zillul Karim1, Reduanul Hasan2, Mohammad Shoeb Abdullah2, Khadiza Tasnim2

+ Author Affiliations

Business & Social Sciences 1 (1) 1-8 https://doi.org/10.25163/business.1110214

Submitted: 22 November 2022 Revised: 10 January 2023  Published: 14 January 2023 


Abstract

Background: This research examines the changing influence of artificial intelligence (AI) technology on marketing with specific attention paid to the influence it has on influencer identification, content curation, and campaign analysis and evaluation. Algorithms under natural language processing (NLP) and machine learning (ML) are rapidly transforming the business world by enabling brands to easily identify suitable influencers through the automation of content customization and ROI computation. Methods: The study takes a qualitative approach by analyzing secondary data such as recent peer-reviewed articles, industry reports, white papers, and others. In addition, several case studies were conducted to assess the application of AI technology in marketing through influencers. Results: The results collected from the interviews highlight that AI tools in general perform far better than traditional systems in almost all areas of influencer marketing. The determined relevancy of target influencers concerning to their audiences increased campaign performance. AI utilized content creation led to better response rates owing to responsiveness to prevailing trends and higher levels of personalization. AI’s real-time learning abilities enables it to alter strategy implementation to achieve the most favorable results within digital ecosystems. Conclusion: AI technology is increasingly becoming an essential element of modern marketing and influencer strategy. Decision-making processes, customized content creation, and effortless influencer profiling can all be automated, enabling AI to forge more meaningful connections between brands and consumers. However, the application of AI does present some difficulties concerning the use and safeguarding of sensitive data, algorithmic bias, and the authenticity of synthetic influencers.

Keywords: Influencer marketing, artificial intelligence, AI integration, social media platforms, influencer selection, campaign optimization.

References


Alotaibi, E. (2020). Application of machine learning in the hotel industry: a critical review. Journal of Association of Arab Universities for Tourism and Hospitality, 18(3), 78-96.

Berbekova, A., Uysal, M., & Assaf, A. G. (2021). A thematic analysis of crisis management in tourism: A theoretical perspective. Tourism Management, 86, 104342.

Boch, A., Hohma, E., & Trauth, R. (2022). Towards an accountability framework for AI: Ethical and legal considerations. Institute for Ethics in AI, Technical University of Munich: Munich, Germany.

Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: using artificial intelligence for customer service. Journal of Hospitality and Tourism Technology, 13(3), 386-403.

Busulwa, R., Pickering, M., & Mao, I. (2022). Digital transformation and hospitality management competencies:

Chugh, A., Patnana, A. K., Kumar, P., Chugh, V. K., Khera, D., & Singh, S. (2020). Critical analysis of methodological quality of systematic reviews and meta-analysis of antibiotics in third molar surgeries using AMSTAR 2. Journal of Oral Biology and Craniofacial Research, 10(4), 441-449.

Ding, X., Fort, T., Redding, S., & Schott, P. (2022). Structural Change Within versus Across Firms: Evidence from the United States. https://doi.org/10.3386/w30127

Egan, D., & Haynes, N. C. (2019). Manager perceptions of big data reliability in hotel revenue management decision making. International Journal of Quality & Reliability Management, 36(1), 25-39.

Feilhauer, S., & Hahn, R. (2021). Formalization of firms’ evaluation processes in cross-sector partnerships for sustainability. Business & Society, 60(3), 684-726.

Fuchs, M., Höpken, W., & Lexhagen, M. (2014). Big data analytics for knowledge generation in tourism destinations A case from Sweden. Journal of destination marketing & management, 3(4), 198-209.

Gkikas, D. C., & Theodoridis, P. K. (2021). AI in Consumer Behavior. In Learning and analytics in intelligent systems (pp. 147–176). https://doi.org/10.1007/978-3-030-80571-5_10

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, 3, 119–132. https://doi.org/10.1016/j.ijin.2022.08.005

Holston-Okae, B. L. (2018). The effect of employee turnover in the hospitality industry: Quantitative correlational study. International Journal of Learning and Development, 8(1), 156-183.

Joshi, V., Reddy, A., Joshi, M., & Chopra, N. (2022b, February 23). Leveraging machine learning algorithms and natural language processing for enhanced AI-Driven influencer campaign analytics. https://aaairj.com/index.php/v1/article/view/9

Kapitan, S., Van Esch, P., Soma, V., & Kietzmann, J. (2021). Influencer marketing and authenticity in content creation. Australasian Marketing Journal (AMJ), 30(4), 342–351. https://doi.org/10.1177/18393349211011171

Kaustubha, K. (Ed.). (2021). Understanding World Media. KK Publications.

Koseoglu, M. A., Yick, M. Y. Y., King, B., & Arici, H. E. (2022). Relational bibliometrics for hospitality and tourism research: A best practice guide. Journal of Hospitality and Tourism Management, 52, 316-330.

Kumar, V., Ramachandran, D., & Kumar, B. (2020). Influence of new-age technologies on marketing: A research agenda. Journal of Business Research, 125, 864–877. https://doi.org/10.1016/j.jbusres.2020.01.007

LakshmiKeerthi, P. (2019). Usage of HR Analytics and Challenges Encountered by Singapore Based Companies (Doctoral dissertation, SRI VENKATESWARA UNIVERSITY TIRUPATI).

Lamest, M., & Brady, M. (2019). Data-focused managerial challenges within the hotel sector. Tourism Review, 74(1), 104-115.

Lee, M., Kwon, W., & Back, K. J. (2021). Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making. International Journal of Contemporary Hospitality Management, 33(6), 2117-2136.

Lee, M., Kwon, W., & Back, K. J. (2021). Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making. International Journal of Contemporary Hospitality Management, 33(6), 2117-2136.

Lewis, C., Fischer, S., Weiner, B. J., Stanick, C., Kim, M., et al. (2015). Outcomes for implementation science: An enhanced systematic review of instruments using evidence-based rating criteria.

Ling, S., Zhao, M., & Zhu, Y. Unpacking the Paradox of Profit Margins: An Analysis of Market Concentration and Economic Dynamics in the US Meat Processing Industry.

Mansour, R. M., Rana, M. E., & Al-Maatouk, Q. (2020). A theoretical framework for implementation of cloud computing in the malaysian hospitality industry. International Journal, 9(2), 2277-2286.

Mariani, M., & Baggio, R. (2022). Big data and analytics in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 34(1), 231-278.

Mariani, M., Bresciani, S., & Dagnino, G. B. (2021). The competitive productivity (CP) of tourism destinations: an integrative conceptual framework and a reflection on big data and analytics. International Journal of Contemporary Hospitality Management, 33(9), 2970-3002.

Marieke, D. M. (2021). Global Marketing and Advertising: Understanding cultural paradoxes. SAGE Publications Ltd - Torrossa. https://www.torrossa.com/it/resources/an/5282213

Md Habibur Rahman, Tanjila Islam, Mohammad Hamid Hasan Amjad, Md Shihab Sadik Shovon, Md. Estehad

Mirzaalian, F., & Halpenny, E. (2019). Social media analytics in hospitality and tourism: A systematic literature review and future trends. Journal of Hospitality and Tourism Technology, 10(4), 764-790.

Piroti, M. (2023). Social media influencer marketing and the role of credibility. Theseus. https://www.theseus.fi/handle/10024/813715

Rahman, M. H., Islam, T., Hossen, M. E., Chowdhury, M. E., Hayat, R., Shovon, &. M. S. S., Shabbir, H. -. A. -., Alamgir, M.,

Sharma, A., Patel, N., & Gupta, R. (2022, June 20). Leveraging machine learning algorithms and natural language processing for enhanced AI-Driven influencer campaign analytics. https://eaaij.com/index.php/eaaij/article/view/22

PDF
Abstract
Export Citation

View Dimensions


View Plumx


View Altmetric



0
Save
0
Citation
92
View
0
Share