Consumers’ online shopping choices and assortment forecasting by ABC analysis using eye tracking technology
Amid the thriving e-commerce, traditional marketing methods are getting obsolete in examining consumer behaviour. Using the case study of cheese, the paper aims to reveal peculiarities of forecasting consumers’ online shopping choices with the help of eye-tracking technology. The concept of sensory...
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| Format: | Article |
| Language: | English |
| Published: |
Ural State University of Economics
2025-03-01
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| Series: | Управленец |
| Subjects: | |
| Online Access: | https://upravlenets.usue.ru/en/issues-2025/1728 |
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| Summary: | Amid the thriving e-commerce, traditional marketing methods are getting obsolete in examining consumer behaviour. Using the case study of cheese, the paper aims to reveal peculiarities of forecasting consumers’ online shopping choices with the help of eye-tracking technology. The concept of sensory marketing constitutes the methodological basis of the study. The evi dence base was formed by the results of a neuromarketing experiment (30 experimental subjects) on investigating three online stores with different shelf space allocation (low, middle or high density of products). The research employs general scientific and economic-statistical methods, as well as neurophysiological methods to assess consumers’ reaction during the visual examina tion of goods on the stores’ virtual shelves. Having analysed eye movement patterns, we determined gender differences in view ing web pages. The visual reaction to a product expressed in the maximum number of fixations was found to be a determining metric that allows predicting consumer choice when shopping online. The products were ranked according to the likelihood of them being chosen by consumers based on ABC analysis that was tested using online pages with low and medium product density. The results showed that the number of fixations on products on the virtual shelf is associated with cognitive consumer behaviour when making a choice. The proposed method allows predicting consumers’ online shopping choices, which can help manufacturers more rationally plan their assortment and inventory and effectively promote products in a virtual environment. |
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| ISSN: | 2218-5003 2686-7923 |