In this study, we propose a practical approach to creating a chatbot on the basis of data accumulated by customer support operations. The selected use case is a typical representative of a chatbot application in customer service centers that want to improve their efficiency and raise customer satisfaction. We show how company support information and logs from support interactions can serve as source data for creating a customer support chatbot. The chatbot developed in this use case is targeted at Latvian-speaking users and demonstrates an implementation of Q&A functionality in the Latvian language. We also propose a simple evaluation metric for chatbot responses to natural language questions. As practical chatbots cannot be perfect in providing appropriate answers to all user questions, this metric can be used to assess the readiness of the chatbot for being released to real users. In our experiment, a chatbot with a score of 0.45 showed positive results in a user survey.