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Market Trends and Customer Segmentation for Data of Electronic Retail Store

  • Carlos Rodriguez-PardoEmail author
  • Miguel A. PatricioEmail author
  • Antonio BerlangaEmail author
  • Jose M. MolinaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10334)

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.

Keywords

Postal Code Visualization Technique Price Range Data Mining Method Individual Customer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially funded by projects MINECO TEC2014-57022-C2-2-R, TEC2012-37832-C02-01.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Applied Artificial Intelligence GroupUniversity Carlos III of MadridMadridSpain

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