Generational dynamics of omnichannel customers: analysing shopping preferences across diverse product types

Purpose This study explores the shopping orientations of omnichannel customers through the lens of generational cohort theory, which influences their decision-making style while shopping online. It offers key insights into how Generations X, Y and Z interact with digital platforms, helping retailers adapt to the shifting dynamics of modern customers. Design/methodology/approach Using different customer decision-making styles, a comprehensive questionnaire was administered to a diverse sample selected via systematic probability sampling. The responses were analysed using multivariate and post hoc analysis to uncover generational and product-based differences in online shopping orientations. Findings The analysis reveals apparent generational differences. Gen Z is driven by affordability and quality, while Gen Y is brand-conscious and willing to pay premium prices. In contrast, Gen X exhibits strong brand loyalty, although younger generations show a decline in brand attachment. These findings suggest that retailers must blend online and offline channels to boost customer engagement and loyalty, especially among omnichannel customers. Research limitations/implications The study relies on self-reported data, introducing the potential for recall bias, which could affect the accuracy of reported behaviours. Practical implications Understanding different generational cohorts’ distinct online shopping behaviours empowers marketers and retailers to craft personalised strategies that enhance customer engagement and drive brand loyalty and satisfaction. By tailoring experiences to the unique preferences of each generation, retailers can ensure seamless shopping journeys that resonate across product categories, maximising their market impact and customer retention. Originality/value By applying generational cohort theory, this study uniquely examines the underexplored group of omnichannel customers, offering fresh insights through multivariate analysis into how generational cohorts and product types shape online shopping behaviour, providing valuable guidance for retailers.