The Expectation confirmation model (ECM) is commonly employed to investigate technological advances and customer satisfaction with chatbots. However, customer satisfaction is a multifaceted concept intertwined with emotions and subjective perceptions, comprehending customer satisfaction fully can therefore be challenging. Consequently, the purpose of this exploratory study was to develop and refine the concept of customer satisfaction by answering the research question: How does the integration of underlying factors to the Expectation Confirmation Model (ECM) affect customer satisfaction with chatbot services?. The study incorporated underlying factors such as anthropomorphic behavior, brand perception, trust and word of mouth, which were integrated into the existing components of the ECM. Through a unique research approach involving 20 semi-structured interviews and observations, this study captured and reflected on the subjective impressions and emotions of customers while using chatbots. An array of findings are presented, such as the importance of distinguishing between usability and problem-solving efficiency of chatbots performance, the emphasis on accurate answers over human-like characteristics for chatbots, and the impact of experience, familiarity and age on customer satisfaction with chatbots. In conclusion, this study advocates for further qualitative research to explore  the potential impact of other underlying factors' on customer satisfaction for ECM.