Chatbots for customer service have been widely studied in many different fields, ranging from Natural Language Processing (NLP) to Communication Science. These fields have developed different evaluation practices to assess chatbot performance (e.g., fluency, task success) and to measure the impact of chatbot usage on the user’s perception of the organisation controlling the chatbot (e.g., brand attitude) as well as their willingness to enter a business transaction or to continue to use the chatbot in the future (i.e., purchase intention, reuse intention). While NLP researchers have developed many automatic measures of success, other fields mainly use questionnaires to compare different chatbots. This paper explores the extent to which we can bridge the gap between the two, and proposes a research agenda to further explore this question.