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ALGORITHMIC GUERRILLA: AI-POWERED ADVERTISING AND TRANSFORMING CONSUMER EXPERIENCE.

  • Published In: International Journal of Turcologia, 2025, v. 20, n. 40. P. 50 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: DEMİRCİ HACIOĞLU, Hilal 3 of 3

Abstract

The rise of digital technologies and data processing capabilities has fundamentally transformed marketing communications and advertising practices. In this study, the "element of surprise" principle of traditional guerrilla marketing, combined with Artificial Intelligence (AI) and machine learning technologies, is addressed and defined as "Algorithmic Guerrilla." In this context, the study aims to examine how AI-powered guerrilla marketing applications transform the advertising landscape and consumer experience. Adopting a case study design within qualitative research methods, the research analyzes Burger King's "Burn That Ad" campaign as a global example and the "Alkazar Rüyası" (Alkazar Dreams) project by the Nike and Refik Anadol collaboration as a local example. The findings indicate that technology can be utilized in marketing communications as both a "destructive" (competition-oriented) and a "constructive" (art/experience-oriented) tool. However, the potential for these interactive experiences to trigger new debates regarding data privacy and ethical consent within the context of "surveillance capitalism" is also addressed within the scope of the research. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Turcologia. 2025/09, Vol. 20, Issue 40, p50
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1956-2543
  • Accession Number:190836803
  • Copyright Statement:Copyright of International Journal of Turcologia is the property of International Journal of Turcologia and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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