Abstract: A method for customer churn characterization based on LightBGM (Light Gradient Boosting Machine) is proposed. Additionally, experimental approaches for mitigation of churn are conducted through churn prediction. The experiments reveal several churn characteristics such as age dependency, gender dependency (with a high divorce rate among female customers), number of visits dependency (with a higher churn rate for customers with fewer visits), unit price (per hair salon visit) dependency (with a higher withdrawal rate for lower-priced services), date of first visit dependency (with a high churn rate for recent customers), date of last visit dependency, and menu dependency (with low attrition rates for gray hair dye and high attrition rates for school and child cuts) and so on. Through the experiments, these dependencies are clarified. It is found that the first visit date is the most significant factor for churn customer character. Also, it is found that “distance to hair salon” dependency may be related to the availability of parking lots, although this factor has insignificant impact on the churn rate.

Kohei Arai, Ikuya Fujikawa, Yusuke Nakagawa, Ryoya Momozaki and Sayuri Ogawa, “Method for Characterization of Customer Churn Based on LightBGM and Experimental Approach for Mitigation of Churn” International Journal of Advanced Computer Science and Applications(IJACSA), 14(6), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140613

@article{Arai2023,
title = {Method for Characterization of Customer Churn Based on LightBGM and Experimental Approach for Mitigation of Churn},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140613},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140613},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {6},
author = {Kohei Arai and Ikuya Fujikawa and Yusuke Nakagawa and Ryoya Momozaki and Sayuri Ogawa}
}