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Which Photographic Features of Product Images Impact Consumer Attractiveness?
- 1 Department of Mathematics & Statistics, McMaster University, Canada
* Author to whom correspondence should be addressed.
Abstract
The determinants influencing online shopping decisions have long been a focal point of interest for both business practitioners and academic researchers. Among these factors, product imagery stands out as a critical element. However, there remains a notable research gap in understanding the specific features of product images that significantly impact consumers' purchasing decisions in the online context. While the role of product imagery is acknowledged, further investigation is needed to identify which particular aspects of these images are most influential in shaping consumer decision-making processes. The majority of previous research about product images used survey-based methods to measure image quality based on interviewee’s satisfaction and rating instead of data-based analysis. Hence, this research paper aims to investigate the relationship between product photography and customer attractiveness on e-commerce platforms by exploring what photographic characteristics could contribute to better designing product images that captivate consumers and ultimately enhance sales. Additionally, this study aims to explore potential differences in purchasing behavior between male and female consumers, providing a complementary dimension to the research findings. The analysis is conducted using data-driven methodologies, with a specific focus on key features of product images. These include aesthetic appeal, embedded messaging, and social presence, all of which are central to the investigation's scope. The author collects data through a crawler tool and organizes it into a raw dataset (both for males and females). Next, image-processing techniques and feature engineering are applied to conduct the final dataset used for linear regression. Then, backward elimination contributes to determining the best-performed linear regression model, which illustrates the photographic features which are significant to the impingement of sales numbers. As a result, it is confirmed that male clients are more affected by the amount of information contained and the proportion of the products in the product image. In contrast, female clients take notice of the appearance of human models.
Keywords
Image-processing, Machine Learning, Product Photography, Consumer Behavior, E-Commerce
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Cite this article
Yang,X. (2025). Which Photographic Features of Product Images Impact Consumer Attractiveness?. Advances in Economics, Management and Political Sciences,168,83-91.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 4th International Conference on Business and Policy Studies
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