  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.
