Task-oriented chatbots are becoming popular alternatives for fulfilling users' needs, but few studies have investigated how users cope with conversational 'non-progress' (NP) in their daily lives. Accordingly, we analyzed a three-month conversation log between 1,685 users and a task-oriented banking chatbot. In this data, we observed 12 types of conversational NP; five types of content that was unexpected and challenging for the chatbot to recognize; and 10 types of coping strategies. Moreover, we identified specific relationships between NP types and strategies, as well as signs that users were about to abandon the chatbot, including 1) three consecutive incidences of NP, 2) consecutive use of message reformulation or switching subjects, and 3) using message reformulation as the final strategy. Based on these findings, we provide design recommendations for task-oriented chatbots, aimed at reducing NP, guiding users through such NP, and improving user experiences to reduce the cessation of chatbot use.