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PurposeDespite the rapid adoption of smartphones among digital fashion consumers, their attitude to retailers' mobile apps and websites is one of increasing dissatisfaction. This suggests that understanding how mobile consumers use smartphones for fashion shopping is important in developing digital shopping platforms that fulfil consumer' expectations.Design/methodology/approachFor this research, mobile eye-tracking technology was employed in order to develop unique shopping journeys for 30 consumers, using fashion retailers' websites on smartphones, documenting their differences and similarities in browsing and purchasing behaviour.FindingsBased on scan path visualisations and observed shopping experiences, three prominent mobile shopping journeys and shopper types were identified: “directed by retailer's website”, “efficient self-selected journey” and “challenging shopper”. These prominent behaviour patterns were used to characterise mixed cluster behaviours; three distinct mixed clusters were identified, namely, “extended self-selected journey”, “challenging shoppers directed by retailer's website” and “focused challenging shopper”.Research limitations/implicationsThis research argues that mobile consumers can be segmented based on their activities and behaviours on the mobile website. Knowing the prominent shopping behaviour types any other complex behaviour patterns can be identified, analysed and described.Practical implicationsThe findings of this research can be used in developing personalised shopping experiences on smartphones by feeding these shopper types into retailers' digital marketing strategy and artificial intelligence (AI) systems.Originality/valueThis paper contributes to consumer behaviour literature by proposing a novel mobile consumer segmentation approach based on detailed shopping journey analysis using mobile eye-tracking technology.

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With exponential adoption of mobile devices, consumers increasingly use them for shopping. There is a need to understand the gender differences in mobile consumer behavior. This study used mobile eye tracking technology and mixed-method approach to analyze and compare how male and female mobile fashion consumers browse and shop on smartphones. Mobile eye tracking glasses recorded fashion consumers' shopping experiences using smartphones for browsing and shopping on the actual fashion retailer's website. 14 participants successfully completed this study, half of them were males and half females. Two different data analysis approaches were employed, namely a novel framework of the shopping journey, and semantic gaze mapping with 31 Areas of Interest (AOI) representing the elements of the shopping journey. The results showed that male and female users exhibited significantly different behavior patterns, which have implications for mobile website design and fashion m-retail. The shopping journey map framework proves useful for further application in market research. CCS CONCEPTS • Human-centered computing → Smartphones; Empirical studies in ubiquitous and mobile computing; Empirical studies in interaction design; • Information systems → Online shopping; • Applied computing → Online shopping; Marketing; Decision analysis; • Social and professional topics → User characteristics; Men; Women.

The impact of COVID-19 on shopping behaviour preferences has resulted in the accelerated adoption of e-commerce and increased traffic of first-time e-commerce shoppers worldwide. This study compared experienced versus inexperienced mobile consumers' shopping experiences on smartphones. A mixed-methods research, combining mobile eye-tracking technology and interviews, was employed. The comparison of experienced and inexperienced users showed significant differences in regards to time spent on various stages of the shopping journey, used elements of the website and problem areas encountered. Inexperienced users have higher expectations towards fashion retailer's website. Mobile consumers' prior experience using retailers' digital shopping platform is a key parameter in user experience research and participants' recruitment. The findings of this research have managerial and methodological implications and can be used in understanding the behaviour differences between current and potential customers, and in developing personalised shopping experiences on smartphones by feeding these into retailers' digital analytics database and marketing strategy.