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Evaluation of Varying Visual Intensity and Position of a Recommendation in a Recommending Interface Towards Reducing Habituation and Improving Sales

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Advances in E-Business Engineering for Ubiquitous Computing (ICEBE 2019)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 41))

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Abstract

The abundance of advertising in e-commerce results in limited user attention to marketing-related content on websites. As far as recommender systems are concerned, presenting recommendation items in a particular manner becomes equally relevant as the underlying product selection algorithms. To enhance content presentation effectiveness, marketers experiment with layout and visual intensity of website elements. The presented research investigates those aspects for a recommending interface. It uses a quantitative research methodology involving gaze tracking for implicit monitoring of human-website interaction in an experiment instrumented for a simple-structure recommending interface. The experimental results are discussed from the perspective of the attention attracted by recommended items in various areas of the website and with varying intensity, while the main goal is to provide advice on the most viable solutions.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, ul. Zolnierska 49, 71-210, Szczecin, Poland

    Piotr Sulikowski

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  1. Piotr Sulikowski
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Correspondence to Piotr Sulikowski .

Editor information

Editors and Affiliations

  1. ECB, Faculty of Engineering and Computing, Coventry University, Coventry, UK

    Kuo-Ming Chao

  2. School of Software, Shanghai Jiaotong University, Shanghai, China

    Lihong Jiang

  3. School of Business, University of New South Wales, Canberra, ACT, Australia

    Omar Khadeer Hussain

  4. National Taiwan Ocean University, Keelung City, Taiwan

    Shang-Pin Ma

  5. Faculty of Engineering and Computing, Coventry University, Coventry, UK

    Xiang Fei

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Sulikowski, P. (2020). Evaluation of Varying Visual Intensity and Position of a Recommendation in a Recommending Interface Towards Reducing Habituation and Improving Sales. In: Chao, KM., Jiang, L., Hussain, O., Ma, SP., Fei, X. (eds) Advances in E-Business Engineering for Ubiquitous Computing. ICEBE 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-030-34986-8_15

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