The current research demonstrates how conversational robo advisors as opposed to static, non-conversational robo advisors alter perceptions of trust, the evaluation of a financial services firm, and consumer financial decision making. We develop and empirically test a novel conceptualization of conversational robo advisors building on prior work in human-to-human communication and interpersonal psychology, showing that conversational robo advisors cause greater levels of affective trust compared to non-conversational robo advisors and evoke a more benevolent evaluation of a financial services firm. We demonstrate that this increase in affective trust not only affects firm perception (in terms of benevolence attributions or a more positively-valenced onboarding experience), but has important implications for investor behavior, such as greater recommendation acceptance and an increase in asset allocation toward conversational robo advisors. These findings have important implications for research on trust formation between humans and machines, the effective design of conversational robo advisors, and public policy in the digital economy.

Voice-based interfaces provide new opportunities for firms to interact with consumers along the customer journey. The current work demonstrates across four studies that voice-based (as opposed to text-based) interfaces promote more flow-like user experiences, resulting in more positively-valenced service experiences, and ultimately more favorable behavioral firm outcomes (i.e., contract renewal, conversion rates, and consumer sentiment). Moreover, we also provide evidence for two important boundary conditions that reduce such flow-like user experiences in voice-based interfaces (i.e., semantic disfluency and the amount of conversational turns). The findings of this research highlight how fundamental theories of human communication can be harnessed to create more experiential service experiences with positive downstream consequences for consumers and firms. These findings have important practical implications for firms that aim at leveraging the potential of voice-based interfaces to improve consumers’ service experiences and the theory-driven “conversational design” of voice-based interfaces.

The implementation of bot interfaces varies tremendously in current industry practice. They range from the human-like to those that merely present a brand logo or a digital avatar. Some applications provide a maximum amount of information with limited turn-taking between the user and the interface; others offer only short pieces of information and require more turn-taking. Instead of simply implementing the default option provided by chatbot providers and platforms, companies should consider very carefully how the specifics of the chatbot interface might affect the user experience. Simple mechanics such as increasing the frequency of interactions leads to greater trust and a more enjoyable user experience. Also, personalizing chatbots with basic consumer characteristics such as gender increases trust and improves the perceived closeness between the customer and the chatbot – and ultimately the brand. Brand managers should therefore consider chatbots not as merely another digital marketing fad or a way to save costs through service automation. When implemented wisely, they are even able to increase a company’s upselling potential.

This research shows that AI-based conversational interfaces can have a profound impact on consumer-brand relationships. We develop a conceptual model of verbal embodiment in technology-mediated communication that integrates three key properties of human-to-human dialogue – (1) turn-taking (i.e., alternating contributions by the two parties), (2) turn-initiation (i.e., the act of initiating the next turn in a sequence), and (3) grounding between turns (i.e., acknowledging the other party’s contribution by restating or rephrasing it). These fundamental conversational properties systematically shape consumers’ perception of an AI-based conversational interface, their perception of the brand that the interface represents, and their behavior in connection with that brand. Converging evidence from four studies shows that these dialogue properties enhance the perceived humanness of the interface, which in turn promotes more intimate consumer-brand relationships and more favorable behavioral brand outcomes (greater recommendation acceptance, willingness to pay a price premium, brand advocacy, and brand loyalty). Moreover, we show that these effects are reduced in contexts requiring less mutual understanding between the consumer and the brand. This research highlights how fundamental principles of human-to-human communication can be harnessed to design more intimate consumer-brand interactions in an increasingly AI-driven marketplace.

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