A system and method of combining table management software and customer experience skills by generating profiles of patrons, servers, and restaurants and using machine learning algorithms on those profiles to build more intimate relationships between patrons, food service establishments, and food service professionals. Trait matching provides optimized matchmaking between patrons and servers who share certain commonalities while also balancing the table management operations. Machine learning algorithms may be used to identify patterns of commonality that would not otherwise be recognized. This system allows patrons to choose servers at an establishment over a plurality of electronic devices by using the cluster analysis results. It provides servers more lateral work experience between participating restaurants, and restaurants more power to operate smoothly and build highly cohesive teams.