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Research on Conveying User Experiences Through Digital Advertisement

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Human Interface and the Management of Information. Information Presentation and Visualization (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12765))

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Abstract

Digital advertisement enables potential consumers to picture what they might experience when they use an advertised product. Creating effective user experience (UX) images in digital advertisement helps companies promote their products and attract specific audiences while allowing the designer of the product to communicate their vision to viewers. To increase the efficacy of advertising while simplifying the design processes, it is important to establish the designer’s own visualization of the product to communicate to buyers. In this research, we conducted an evaluative experiment by analyzing the objective features of 80 video advertisements for home appliances to create an evaluative prediction model for the 24 defined types of UX. The results revealed that UX can be conveyed through digital media and that objective features, which are mainly related to people’s appearance, visual, audio, and content, can influence this. Each UX prediction model was created with different features and might be used as a reference in creating digital content advertisements that convey the UX.

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Authors and Affiliations

  1. Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Kanagawa, Japan

    Stephanie Dwiputri Suciadi & Miwa Nakanishi

Authors
  1. Stephanie Dwiputri Suciadi
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  2. Miwa Nakanishi
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Corresponding author

Correspondence to Stephanie Dwiputri Suciadi .

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Editors and Affiliations

  1. Tokyo University of Science, Tokyo, Saitama, Japan

    Sakae Yamamoto

  2. Tokyo City University, Tokyo, Japan

    Hirohiko Mori

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Dwiputri Suciadi, S., Nakanishi, M. (2021). Research on Conveying User Experiences Through Digital Advertisement. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information. Information Presentation and Visualization. HCII 2021. Lecture Notes in Computer Science(), vol 12765. Springer, Cham. https://doi.org/10.1007/978-3-030-78321-1_2

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  • DOI: https://doi.org/10.1007/978-3-030-78321-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78320-4

  • Online ISBN: 978-3-030-78321-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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