Customer Segmentation Based on RFM Attributes Using Machine Learning

Author:

Khanfar Iyad,Khanfar Isra,Odeh Mahmoud

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Tripathi, S., Bhardwaj, A., Poovammal, E.: Approaches to clustering in customer segmentation. Int. J. Eng. Technol. 7(3,12), 802–807 (2018)

2. Doğan1, O., Ayçin, E., Atıl Bulut, Z.: Customer Segmentation by Using RFM model and Clustering methods: A case study in retail industry. Int. J. Contemp. Econ. Adm. Sci. 8(1), 1–19 (2018). ISSN: 1925-4423

3. Koul, S., Philip, T.M.: Customer segmentation techniques on e-commerce. In: 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) Department of Electrical & Electronics Engineering, Galgotias College of Engineering and Technology, Gr. Noida, India (2021)

4. Dzulhaq, M.I., Sari, K.W., Ramdhan, S., Tullah, R., S., Customer segmentation based on RFM value using K-means algorithm. IEEE Explore (2019)

5. Tabiana, K., Velu, S., Ravi, V.: K-means clustering approach for intelligent customer segmentation using customer purchase behavior data. MDPI Sustain. 14(7243), 2022 (2022)

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