Experiential retailing leveraged by data analytics

Abstract

The purpose of the study is to establish how in retail industry consumer data can be leveraged and analysed to provide customers an enhance shopping experience. Popular machine learning algorithms related to text mining AIDS in parsing the natural language and helps to understand the brand image and what the brand currently is lacking. In the last decade, although ecommerce brought a revolution in retail industry, shopping trends show that consumers spend more in offline store than online. The rise of omni-channel retailing and data-driven decision-making are shifting retailer focus to providing enhanced in-store customer experiences. Retailers are trying to find ways to stand out in the highly competitive environment. The solution to this problem is providing retailtainment. This study helps to understand how the available customer data is to be analysed to create unique experiences and enable experience-based stores. The results of this study will help a retail company understand how omnichannel play an important role creating customer engagement strategies.