When customers are interested in a Service or intend to buy it, they sometimes have questions on that Service. In this study, we considered an inquiry System in which customers ask questions on a specific Service and obtain correct information on the Service. For such an inquiry System, a question-answering (Q&A) technology is needed. Many programming modules for such a technology have been developed and can be easily used for System development. In many Q&A technologies, machine-learning techniques are involved, and we need to prepare training data consisting of pairs of an answer and assumed questionS. For training-data preparation, an answer set for a Service should be defined as the first step and the answer set should cover all the information on the Service that customers may ask about. By using a customer-behavior model and introducing a Service-function model, we propose a method of effectively collecting knowledge information for an answer set on a Service. Through a case study, we show that we can collect exhaustive knowledge information for an answer set with our method compared to the case in which domain experts collect knowledge information in their own way. For an actual project, we also considered an actual inquiry-System-development project, with training data obtained with the proposed method, and showed that the System covers almost all the information on the Service that customers may ask after a user test.