Abstract
Data analysis is comprised of a set of processes that allows a key support for making better decisions. The ability to analyse data in the field of retail trade allows companies to obtain valuable information such as understanding the profile of customers who demand a particular type of product, optimizing the price of certain products, identifying customers interested in such products and analysing the best way to approach them. This paper will present results obtained during the development of an analysis process on the data of an electronic retail store. The analysis will show the results obtained and validated by end users using different visualization techniques. Finally, the result of applying client segmentation using self-organized maps and the interpretation of their results in a visual way will be discussed.
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Acknowledgments
This work was partially funded by projects MINECO TEC2014-57022-C2-2-R, TEC2012-37832-C02-01.
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Rodriguez-Pardo, C., Patricio, M.A., Berlanga, A., Molina, J.M. (2017). Market Trends and Customer Segmentation for Data of Electronic Retail Store. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_44
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DOI: https://doi.org/10.1007/978-3-319-59650-1_44
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