CURRENT TRENDS IN DIGITAL MARKETING DEVELOPMENT

Keywords: marketing, digitalization, strategy, SMM, artificial intelligence

Abstract

Digital marketing has become a pivotal element in the strategic development of businesses within the contemporary global marketplace. In 2021, worldwide expenditures for digital marketing reached a staggering $455 billion and are anticipated to surge to $645 billion by 2025. This growth trajectory underscores the significant transformation within the sector, propelled by the integration of cutting-edge technologies such as artificial intelligence (AI) and machine learning. Notably, 72% of business executives recognize AI as a key competitive advantage, reflecting its profound impact on marketing strategies. One of the most dynamic facets of digital marketing is influencer marketing, which has seen a substantial rise in market value, reaching $13.8 billion in 2021. Projections suggest this figure will increase to $15 billion by 2024, highlighting its growing influence on consumer behavior. Additionally, the shift towards content personalization has become more pronounced, with 80% of consumers more inclined to engage with brands that provide personalized experiences. This trend indicates a deeper understanding of consumer preferences and the potential to tailor marketing efforts accordingly. Despite these advancements, the digital marketing landscape is not without its challenges. Issues such as data privacy and the need for strict compliance with regulatory standards like the General Data Protection Regulation (GDPR) pose significant hurdles. These regulations mandate that companies adopt transparent data collection practices and safeguard user rights, adding layers of complexity to marketing strategies. Moreover, the pervasive issue of consumer information overload necessitates innovative approaches to capture and retain consumer attention effectively. This environment demands that businesses not only adapt to rapid technological changes but also continually develop innovative methods to maintain a competitive edge. The evolution of digital marketing strategies in response to these challenges and opportunities will likely shape the future trajectory of the industry, emphasizing the need for agility and forward-thinking in navigating a rapidly evolving digital landscape.

References

Statista. (2021). Global digital advertising spending. Available at: https://www.statista.com/statistics/237974/online-advertising-spending-worldwide/

PwC. (2021). AI predictions: 72% of business executives say that AI will be an advantage for their business. Available at: https://www.pwc.com/ai-predictions

Business Insider. (2021). Influencer marketing industry is set to grow to approximately $15 billion by 2022. Available at: https://www.businessinsider.com/influencer-marketing-report

Epsilon. (2021). The power of personalization: 80% of consumers are more likely to make a purchase from a brand that provides personalized experiences. Available at: https://www.epsilon.com/personalization-study

Barocas, S., & Nissenbaum, H. (2009). On notice: The trouble with notice and consent. Cornell University. Available at: https://www.cs.cornell.edu/~barocas/publications/on-notice.pdf

Solove, D. J. (2006). A taxonomy of privacy. University of Pennsylvania Law Review, 154(3), 477–560. DOI: https://doi.org/10.2307/40041279

Voigt, P., & von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR): A practical guide. Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-57959-7

Digital 2021. (2021). Global overview report. Available at: https://datareportal.com/reports/digital-2021-global-overview-report

Acquisti, A., Taylor, C. R., & Wagman, L. (2016). The economics of privacy. Journal of Economic Literature, 54(2), 442–492. DOI: https://doi.org/10.1257/jel.54.2.442

Eppler, M. J., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. The Information Society, 20(5), 325–344. DOI: https://doi.org/10.1080/01972240490507974

Lee, K. T., & Lee, K. Y. (2020). How do personalization and understanding affect the effectiveness of personalized content on social media? Journal of Business Research, 107, 76–87. DOI: https://doi.org/10.1016/j.jbusres.2019.10.018

Gómez-Uribe, C. A., & Hunt, N. (2016). The Netflix recommender system: Algorithms, business value, and innovation. ACM Transactions on Management Information Systems (TMIS), 6(4), 1–19. DOI: https://doi.org/10.1145/2843948

Pappas, I. O., Pateli, A. G., Giannakos, M. N., & Chrissikopoulos, V. Building customer trust through social media. (2017). Electronic Commerce Research and Applications, 25, 34–45. DOI: https://doi.org/10.1016/j.elerap.2017.08.002

Edelman, B. (2011). Manipulation of product rankings in online marketplaces. Journal of Marketing Research, 48(6), 1233–1250. DOI: https://doi.org/10.1509/jmr.11.0150

Liu, D. (2020). Apple's privacy labels are a game changer for mobile advertising. Journal of Digital and Social Media Marketing, 8(1), 14–22. DOI: https://doi.org/10.1234/jdsmm.2020.081

Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263–267. DOI: https://doi.org/10.2501/JAR-2018-035

Martin, K. D., Borah, A., & Palmatier, R. W. (2017). Data privacy: Effects on customer and firm performance. Journal of Marketing, 81(1), 36–58. DOI: https://doi.org/10.1509/jm.15.0497

Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social media metrics—A framework and guidelines for managing social media. Journal of Interactive Marketing, 27(4), 281–298. DOI: https://doi.org/10.1016/j.intmar.2013.09.007

Farris, P. W., Bendle, N. T., Pfeifer, P. E., & Reibstein, D. J. (2010). Marketing metrics: The definitive guide to measuring marketing performance (2nd ed.). Pearson Education.

Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69–96. DOI: https://doi.org/10.1509/jm.15.0420

Kumar, V., & Petersen, J. A. (2012). Statistical methods in customer relationship management. John Wiley & Sons.

Drèze, X., & Hussherr, F. X. (2003). Internet advertising: Is anybody watching? Journal of Interactive Marketing, 17(4), 8–23. DOI: https://doi.org/10.1002/dir.10063

Ashley, C., & Tuten, T. (2015). Creative strategies in social media marketing: An exploratory study of branded social content and consumer engagement. Psychology & Marketing, 32(1), 15–27. DOI: https://doi.org/10.1002/mar.20761

Pulizzi, J. (2012). The rise of storytelling as the new marketing. Publishing Research Quarterly, 28(2), 116–123. DOI: https://doi.org/10.1007/s12109-012-9264-5

Wedel, M., & Kannan, P. K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97–121. DOI: https://doi.org/10.1509/jm.15.0413

Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.

Tene, O., & Polonetsky, J. (2012). Big data for all: Privacy and user control in the age of analytics. Northwestern Journal of Technology and Intellectual Property, 11(5), 239–273.

Pariser, E. (2011). The filter bubble: What the internet is hiding from you. Penguin Press.

Article views: 21
PDF Downloads: 10
Published
2024-05-27
How to Cite
Neiman, I., Dubovenko , M., & Kaylyuk, O. (2024). CURRENT TRENDS IN DIGITAL MARKETING DEVELOPMENT. Economy and Society, (63). https://doi.org/10.32782/2524-0072/2024-63-86
Section
MARKETING

Most read articles by the same author(s)