Customer segmentation is a fundamental process to develop effective marketing strategies, personalize customer experience and boost their retention and loyalty. This problem has been widely addressed in the scientific literature, yet no definitive solution for every case is available. A specific case study characterized by several individualizing features is thoroughly analyzed and discussed in this paper. Because of the case properties a robust and innovative approach to both data handling and analytical processes is required. The study led to a sound proposal for customer segmentation. The highlights of the proposal include a convenient data partition to decompose the problem, an adaptive distance function definition and its optimization through genetic algorithms. These comprehensive data handling strategies not only enhance the dataset reliability for segmentation analysis but also support the operational efficiency and marketing strategies of sports centers, ultimately improving the customer experience.

本文通过分析一个具有个性化特征的特定案例研究，提出了一种对于客户细分的稳健且创新的方法，该方法通过方便的数据划分、自适应距离函数定义以及遗传算法的优化来增强数据集可靠性，从而改进了运营效率和市场营销策略，最终提高了客户体验。

体育中心顾客细分：案例研究