Comparing Data from Chatbot and Web Surveys: Effects of Platform and Conversational Style on Survey Response Quality

This study aims to explore the feasibility of a text-based virtual agent as a new survey method to overcome the web survey's common response quality problems, which are caused by respondents' inattention. To this end, we conducted a 2 (platform: web vs. chatbot) × 2 (conversational style: formal vs. casual) experiment. We used satisficing theory to compare the responses' data quality. We found that the participants in the chatbot survey, as compared to those in the web survey, were more likely to produce differentiated responses and were less likely to satisfice; the chatbot survey thus resulted in higher-quality data. Moreover, when a casual conversational style is used, the participants were less likely to satisfice–although such effects were only found in the chatbot condition. These results imply that conversational interactivity occurs when a chat interface is accompanied by messages with effective tone. Based on an analysis of the qualitative responses, we also showed that a chatbot could perform part of a human interviewer's role by applying effective communication strategies.