AI Chatbots in Customer Service : Adoption Hurdles and Simple Remedies

Despite recent advances in language processing algorithms, chatbot technology continues to face adoption hurdles. We survey chatbot users about their experiences and use their testimonies to construct a decision model of customer choice between the chatbot service channel and the live agent service channel. The fundamentals of this choice are the time spent in line and in service, the chatbot’s success rate, and the qualitative differences in the service experience provided by the chatbot and by the live agent. We then conduct experiments in which participants choose, and then experience, the chatbot or the live agent channel as we vary operational (i.e., times spent and chatbot success rates) and qualitative features of the chatbot. We find that users respond positively to improvements in chatbot operational performance; however, the chatbot channel remains underutilized relative to what expected time minimization would predict. Additional experiments show that this underutilization is caused by two separate mechanisms: algorithm aversion (aversion to an algorithmic service provider), and gatekeeper aversion (aversion to any service format that may involve multiple stages). Examining potential remedies, we find that algorithm aversion can be mitigated by making salient the expected time savings offered by the chatbot. However, gatekeeper aversion is more persistent and harder to overcome. We conclude by building and estimating a structural model of channel demand and by proposing a behavior-aware service design that reduces the firm’s staffing costs by up to 22%