Improving Customer Experience Using Artificial Intelligence in Online Retail

Abstract

Abstract This paper presents research on precursors that can generate unique and attractive retail experiences when using artificial intelligence. Among them are safe technology, ethical aspects, and customer-friendly technology. The motivation for choosing this topic is that it gives a global, current perspective and arouses interest, curiosity, uncertainty, even fear. Quantitative research was implemented with the help of an online questionnaire. The conceptual model derived from the literature was then analysed through regression analysis. Data collected from 272 consumers allowed the research hypotheses to be validated. The results reveal that artificial intelligence applied in retail is the solution for achieving higher performance in the retail field, but without being used unethically. The results provide an overview of AI in retail today, with survey participants expressing confidence in AI’s ability to improve their shopping experience. The originality of the research consists of approaching for the first time in the considered emerging market the perception of consumers toward the vectors that enhance their in-store shopping expectations. Considering the direction in which technology is evolving and based on the arguments of specialists, it can be stated that Artificial Intelligence will represent an element of distinction and competitive advantage. Companies in the retail sector that will invest in the development of Artificial Intelligence will benefit in the long term. Artificial intelligence should not be absent from the retail context, and further investment should be made in its development. The present study did not determine the actual purchase experience in virtual retail stores but was based on a hypothetical situation. Also, this study used a limited sample of respondents, with only Millennials participating. A future research perspective could be based on this study, but using a larger and more representative sample.