Understand omnichannel customer value and the human-machine user experience when using mobile application

Abstract

[EMBARGOED UNTIL 8/1/2023] This research was designed to explore the human-machine user/consumer experience when customers use retail mobile applications under the omnichannel context. Customer reviews from retail mobile application were crawled and investigated by text-mining methods, including textual data pre-processing, LDA topic modeling, sentimental analysis, word co-occurrence network. This is the first attempt to quantify fashion retailing data using text-mining methods to thoroughly investigate the user/consumer experience in omnichannel shopping. Based on the customer value theory and components of the user experience model, the study findings were expected to provide further evidence of the importance of the user experience in human-machine interfaces when adopting omnichannel strategy. The findings would also help to optimize the performance of the retail mobile applications and improve user experience to achieve a seamless omnichannel shopping experience. Meanwhile, the findings help retailers to develop practical strategies to convey consistent customer value via mobile applications, based on their positioning and business features.