Digital Transformation of Advertising: Trends, Strategies, and Evolving User Preferences in Online Advertising

Authors

  • Zimeng Zhou

DOI:

https://doi.org/10.54097/3088d623

Keywords:

Online advertising, Marketing models, User characteristics, Evolution.

Abstract

This study discusses the evolving trends in online advertising, diverse marketing models, and changing user needs. From the early development of the Internet, especially in the early 1990s, to the emergence of numerous advertising formats, online advertising has become an integral part of modern marketing. Different types of online advertisements, such as banner ads, pop-up ads, video ads, native ads, search engine ads, and social media ads, fulfill different needs of advertisers. In addition, the study also explores diverse marketing models for online advertising, including pay-per-click, pay-per-thousand-displays, pay-per-action, affiliate marketing, targeted ads, and video ads, which provide more choices for advertisers. In terms of user characteristics and needs, as technology continues to evolve, user reliance on mobile devices increases, the use of ad-blocking and anti-advertising technologies rises, concerns about data privacy increase, social media becomes an important channel for advertising, and data analytics and ad-tracking technologies become increasingly critical. A user’s age, gender, geographic location, interests, purchase history, device and platform, social interactions, and privacy preferences are important in creating user profiles and target market analysis. In summary, online advertising plays a key role in the modern marketplace, providing advertisers with global advertising opportunities and the need to continually adapt to market and technological changes to maximize ad effectiveness.

Downloads

Download data is not yet available.

References

McStay A. Digital advertising. Bloomsbury Publishing, 2017.

Le T D, Vo H. Consumer attitude towards website advertising formats: A comparative study of banner, pop-up and in-line display advertisements. International Journal of Internet Marketing and Advertising, 2017, 11 (3): 202 - 217.

Chou Y P, Horng S J, Gu H Y, et al. Detecting pop‐up advertisement browser windows using support vector machines. Journal of the Chinese Institute of Engineers, 2008, 31 (7): 1189 - 1198.

Hsieh A Y, Lo S K, Chiu Y P, et al. Do not allow pop-up ads to appear too early: Internet users’ browsing behavior to pop-up ads. Behaviour & Information Technology, 2021, 40 (16): 1796 - 1805.

Asdemir K, Kumar N, Jacob V S. Pricing models for online advertising: CPM vs. CPC. Information Systems Research, 2012, 23(3-part-1): 804 - 822.

Lin M, Ke X, Whinston A B. Vertical differentiation and a comparison of online advertising models. Journal of Management Information Systems, 2012, 29 (1): 195 - 236.

Agarwal M A, Nandal N. Digital Marketing: Paid Internet Advertising and Its Revenue Model. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2020, 11 (2): 720 - 725.

Chatsri T. Strategic marketing analysis: a case study of Spotify. 2021.

Opresnik M O. Effective Online Advertising Strategy. HCI International 2020-Late Breaking Papers: Interaction, Knowledge and social media: 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19 - 24, 2020, Proceedings 22. Springer International Publishing, 2020: 418 - 424.

Wilson A. Social Media Marketing: Ultimate User Guide to Facebook, Instagram, YouTube, Blogging, Twitter, LinkedIn, TikTok, Pinterest. Adidas Wilson, 2020.

Downloads

Published

29-12-2023

How to Cite

Zhou, Z. (2023). Digital Transformation of Advertising: Trends, Strategies, and Evolving User Preferences in Online Advertising. Highlights in Business, Economics and Management, 23, 1224-1229. https://doi.org/10.54097/3088d623