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AI technologies in the analysis of visual advertising messages: survey and application

Author

Listed:
  • Larisa Sharakhina

    (Saint Petersburg Electrotechnical University “LETI”)

  • Irina Ilyina

    (Saint Petersburg Electrotechnical University “LETI”)

  • Dmitrii Kaplun

    (Saint Petersburg Electrotechnical University “LETI”)

  • Tatiana Teor

    (Saint Petersburg Electrotechnical University “LETI”)

  • Valeria Kulibanova

    (RANEPA St. Petersburg (The Branch of the Presidential Academy of National Economy and Public Administration)
    St. Petersburg State University of Economics)

Abstract

Artificial intelligence technologies are improving the marketing toolkit, making it possible to process large amounts of data faster and more efficiently than ever before. Machine learning, a subset of AI, uses algorithms that can predict which ads will be most effective in specific situations, allowing for optimized ad targeting. This research explores the issues of coevolution and distribution of machine and human intelligence in various social practices, including marketing and advertising. The authors describe the key approaches to studying the visual component of advertising and suggest revising traditional methods of analyzing advertising messages. The tracking of biometric data combined with AI-based methods that capture human emotions while viewing video content is proposed as a promising direction for such analysis. This paper presents the results of a pilot study based on analytical face-tracking technology using AI, where the subject of the experiment was the analysis of video fragments that may have an impact on the emotional state of the viewer. The AI software platform used was Amazon Rekognition, and the results show that AI analytics provide the ability to track the level of audience engagement in perceiving video content, which helps to improve communication effectiveness. This allows the use of AI to make recommendations for the development of more directed and engaging advertising messages.

Suggested Citation

  • Larisa Sharakhina & Irina Ilyina & Dmitrii Kaplun & Tatiana Teor & Valeria Kulibanova, 2024. "AI technologies in the analysis of visual advertising messages: survey and application," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(4), pages 1066-1089, December.
    • Handle: RePEc:pal:jmarka:v:12:y:2024:i:4:d:10.1057_s41270-023-00255-1
    DOI: 10.1057/s41270-023-00255-1
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    References listed on IDEAS

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