This paper introduces an examination concerning customer segmentation within the payment services sector, specifically focusing on meal card services. Segmentation plays a vital role in understanding consumer preferences, fostering and enhancing customer relationships, and devising marketing strategies tailored to the needs of customers. Previous studies in literature especially focus on the problem of customer segmentation for only customers’ restaurant preferences, not for the meal card industry. This study generalizes the approach to meal card usage by predicting consumers' preferences for meal card services using customer segmentation algorithms for the first time. A dataset on meal card services provided by a Fintech company in Turkey - a company that aims to develop a customer-oriented marketing strategy system - was used for the analyses. The method k-means was applied by using KNIME for customer segmentation. After the segmentation of the customers, we generated the marketing strategies by understanding the motivation and preferences of individual customers. The predictions helped Fintech company in Turkey to increase the usage of meal card balances by 40% of the total usage and increase the income of the company by 25% per month.