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Inter-Organizational Information Sharing of Customer Data in Retail

As massive online retailers are putting increasing pressure on the traditional brick-and-mortar retailers, new ways to compete for customers is needed. Identifying customers’ behavior and understanding their needs could be a crucial way for firms to improve their competitive advantage. One way to better understand customers could be for retailers to collaborate and aggregate their customer data in order to gain more holistic understandings of customers. This thesis examines on a high-level how customer data is used in retail today and what new value can be generated by collaborating and aggregating customer data, both for businesses as well as for consumers. It then goes on to identify structures of customer data sharing that we observe today and what the underlying factors are for each structure. By projecting how these factors will evolve over time, different scenarios are drawn up of what we might expect to see in the retail industry in the future in terms of customer data sharing. The implications of those projections could possibly open up for new business opportunities, both for entrepreneurs as well as incumbent retailers. Thesis Supervisor: Stuart E. Madnick Title: The John Norris Maguire Professor of Information Technologies and Professor of Engineering Systems