Users' experiences with chatbots: findings from a questionnaire study
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RESEARCH ARTICLE
Users’ experiences with chatbots: findings from a questionnaire study Asbjørn Følstad1 · Petter Bae Brandtzaeg1,2 Received: 4 May 2019 © The Author(s) 2020
Abstract For chatbots to be broadly adopted by users, it is critical that they are experienced as useful and pleasurable. While there is an emerging body of research concerning user uptake and use of chatbots, there is a lack of theoretically grounded studies detailing what constitutes good or poor chatbot user experiences. In this paper, we present findings from a questionnaire study involving more than 200 chatbot users who reported on episodes of chatbot use that they found particularly satisfactory or frustrating. The user reports were analysed with basis in theory on user experience, with particular concern for pragmatic and hedonic attributes. We found that pragmatic attributes such as efficient assistance (positive) and problems with interpretation (negative) were important elements in user reports of satisfactory and frustrating episodes. Hedonic attributes such as entertainment value (positive) and strange and rude responses (negative) were also frequently mentioned. Older participants tended to report on pragmatic attributes more often, whereas younger participants tended to report on hedonic attributes more often. Drawing on the findings, we propose four high-level lessons learnt that may benefit chatbot service providers, and we suggest relevant future research. Keywords Chatbots · User experience · Questionnaire study
Introduction Chatbots are machine agents with which users interact through natural language dialogue, by text or voice [4]. The conversational character of chatbots enables new and potentially more convenient and personal ways to access content and services [20]. Chatbots are employed across a range of application areas, such as customer service [38], health [16], education [19] and personal assistance [37]. While chatbots were initially developed to mimic human conversation [47], often in the form of social chatter, current chatbots are typically task-oriented, enabling their users to achieve specific goals or outcomes [41]. However, current task-oriented chatbots are typically also designed in consideration of the emotional or social aspects of conversational interaction [22]. Furthermore, chatbots developed purely for social interaction or relationship formation still exist as a distinct type of chatbot [42].
* Asbjørn Følstad [email protected] 1
SINTEF, Oslo, Norway
University of Oslo, Oslo, Norway
2
Chatbots are seen as promising by service providers [9]. They allow for efficient interactions with users on private messaging platforms and in virtual assistants, and interactions are familiar and low threshold [20]. For users, chatbots are considered a potentially efficient and enjoyable means of accessing content and services [5, 13]. Conversational interaction with machine agents is also becoming more commonplace due to the substantial uptake of voice assistants [32]. However, the full potential of ch
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