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Customer segmentation: RFM Analysis & K-Means

Description

Customer segmentation and customer clustering are two powerful techniques used in marketing to better understand customers beahvior and tailor marketing strategies to their needs. In this project, we explore how to perform customer clustering with K-Means in Python.

We use the data set provided by the UCI Machine Learning Repository "which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. Many customers of the company are wholesalers."

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Build with

  • Pandas
  • Numpy
  • Pandas Profiling
  • Matplotlib
  • Seaborn
  • Scikit-Learn

Contact

Anne-Gaëlle Sng - annegaelleandco@gmail.com.
Project Link: https://github.com/annegaelle-sng/customer-segmentation-with-kmeans.

Acknowlegment

Daqing Chen, Sai Liang Sain, and Kun Guo, Data mining for the online retail industry: A case study of RFM model-based customer segmentation using data mining, Journal of Database Marketing and Customer Strategy Management, Vol. 19, No. 3, pp. 197–208, 2012 (Published online before print: 27 August 2012. doi: 10.1057/dbm.2012.17).

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