Abstract
Retail business models have evolved over the years to create a value chain that combines multiple channels to interact with customers and suppliers. At the same time, technological advances have enabled the collection of various forms of data which can be used to support managerial decisions. This chapter provides a constructive framework to understand the practice of retail analytics—the data-driven approach to support decisions based on models and quantitative methods—through the dynamic evolution of various channels of what is now referred to as omnichannel retail. This framework is supported with several research examples that illustrate the differences in terms of data, decisions, and methods used in various retail channels, and also show more recent examples of convergence and integration across channels.
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Notes
- 1.
Although not reported here, other surveys were also applied to customers to evaluate service quality and appropriateness of product suggestions. For more information, see Fuenzalida (2017).
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Acknowledgements
Part of this chapter was based on the theses of Renzo Fuenzalida, Andrea Rojas, and Cesar Ferreiro in Industrial Engineering, Universidad de Chile. We thank Stefano Maccioni for help as a research assistant. The authors received financial support from the Complex Engineering Systems Institute (grant CONICYT PIA FB0816) and Fondecyt grant 1181201.
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Goic, M., Olivares, M. (2019). Omnichannel Analytics. In: Gallino, S., Moreno, A. (eds) Operations in an Omnichannel World. Springer Series in Supply Chain Management, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-030-20119-7_6
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