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Apserou, Ioanna (2013) How can Retailers use Big Data to improve Customer Experience? [Dissertation (University of Nottingham only)] (Unpublished)

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Abstract

Big Data nowadays is considered ‘the new oil’ (Shaw, 2013) for businesses, that will ensure smooth running of a business operations. Using Big Data companies can access anything they are interested in and exploit opportunities for improvement. Businesses can collect and use massive amounts of data about their customers, their suppliers, etc. so as to develop strategies to succeed. This dissertation aims to answer the research question on how retailers use Big Data to improve customer experience. Retailers’ main objective is to satisfy their customers by offering them what they desire, not only in terms of features and usability of products and services but also by giving them outstanding customer experience. New technology, the web, mobile application services, surveillance cameras, social media, etc., give the opportunity to retailers to gather data about their customers’ shopping behaviour, their preferences, their needs etc. It also gives great customer experience both online and in-store while customers shop. Besides it can be argued that customer experience can generate more data that can be used to improve customer experience. Customer experience frameworks and theories written by academics are described and explained to understand the theoretical side of customer experience and customer experience management (CEM). Furthermore, an analysis using examples of retail companies that use Big Data techniques follows, to answer the research question. It has been concluded that Big Data raises issues of security and privacy, even though both retailers and customers are benefited from the use of Big Data. In addition despite the fact that Big Data offers actionable insights to retailers to succeed, this is not always the case. Retailers’ control over customers reaches up to a point, since there are other factors that retailers cannot control because of unpredictable consumer behaviour.

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	EP, Services
Date Deposited:	28 Mar 2014 16:52
Last Modified:	19 Oct 2017 13:44
URI:	https://eprints.nottingham.ac.uk/id/eprint/26742

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