Analysis of consumer choice features in the digital environment - Korbut, Krystsina I.; Lavrova, Olga I. (Journal of the Belarusian State University. Economics, 2025)
The article studies the behaviour of consumers of an online store selling durable goods in order to stimulate sales of premium products. The key objective is to build a predictive model that allows for a highly accurate assessment of the likelihood of making the next premium purchase based on big data analytics. The study uses multivariate data analysis methods, in particular, factor analysis (to identify latent patterns of product perception) and cluster analysis (to group users based on information-behavioural strategies). It is established that information involvement (the depth of interaction with reviews and filtering) greatly increases the likelihood of making a premium purchase. The model results make it possible to implement personalised content display, segment the audience for email and push notifications, and take into account regional characteristics and macroeconomic conditions that influence consumer preferences. The hypothesis about the significance of the influence of cognitive factors in making consumer choices in the digital environment is confirmed.
Keywords: consumer behaviour; logistic regression; premium purchase; factor analysis; cluster analysis; big data; digital marketing